mcp_server

Class info

Classes

Name	Children	Inherits
BridgeConfig llmling_agent.mcp_server.tool_bridge Configuration for the ToolManager MCP bridge.		object
MCPClient llmling_agent.mcp_server.client FastMCP-based client for communicating with MCP servers.		object
ToolBridgeRegistry llmling_agent.mcp_server.tool_bridge Registry for managing multiple tool bridges.		object
ToolManagerBridge llmling_agent.mcp_server.tool_bridge Exposes a ToolManager's tools as an MCP server for ACP agents.		object

🛈 DocStrings

MCP server integration for LLMling agent.

BridgeConfig dataclass

Configuration for the ToolManager MCP bridge.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

@dataclass
class BridgeConfig:
    """Configuration for the ToolManager MCP bridge."""

    host: str = "127.0.0.1"
    """Host to bind the HTTP server to."""

    port: int = 0
    """Port to bind to (0 = auto-select available port)."""

    transport: str = "sse"
    """Transport protocol: 'sse' or 'streamable-http'."""

    server_name: str = "llmling-toolmanager"
    """Name for the MCP server."""

host class-attribute instance-attribute

host: str = '127.0.0.1'

Host to bind the HTTP server to.

port class-attribute instance-attribute

port: int = 0

Port to bind to (0 = auto-select available port).

server_name class-attribute instance-attribute

server_name: str = 'llmling-toolmanager'

Name for the MCP server.

transport class-attribute instance-attribute

transport: str = 'sse'

Transport protocol: 'sse' or 'streamable-http'.

MCPClient

FastMCP-based client for communicating with MCP servers.

Source code in src/llmling_agent/mcp_server/client.py

class MCPClient:
    """FastMCP-based client for communicating with MCP servers."""

    def __init__(
        self,
        config: MCPServerConfig,
        sampling_callback: ClientSamplingHandler[Any] | None = None,
        message_handler: MessageHandlerT | MessageHandler | None = None,
        accessible_roots: list[str] | None = None,
        tool_change_callback: Callable[[], Awaitable[None]] | None = None,
        prompt_change_callback: Callable[[], Awaitable[None]] | None = None,
        resource_change_callback: Callable[[], Awaitable[None]] | None = None,
    ) -> None:
        # Mutable handler swapped per call_tool for dynamic elicitation
        self._current_elicitation_handler: ElicitationHandler | None = None
        self.config = config
        self._sampling_callback = sampling_callback
        # Store message handler or mark for lazy creation
        self._message_handler = message_handler
        self._accessible_roots = accessible_roots or []
        self._tool_change_callback = tool_change_callback
        self._prompt_change_callback = prompt_change_callback
        self._resource_change_callback = resource_change_callback
        self._client = self._get_client(self.config)

    @property
    def connected(self) -> bool:
        """Check if client is connected by examining session state."""
        return self._client.is_connected()

    async def __aenter__(self) -> Self:
        """Enter context manager."""
        try:
            # First attempt with configured auth
            await self._client.__aenter__()  # type: ignore[no-untyped-call]

        except Exception as first_error:
            # OAuth fallback for HTTP/SSE if not already using OAuth
            if not isinstance(self.config, StdioMCPServerConfig) and not self.config.auth.oauth:
                try:
                    with contextlib.suppress(Exception):
                        await self._client.__aexit__(None, None, None)  # type: ignore[no-untyped-call]
                    self._client = self._get_client(self.config, force_oauth=True)
                    await self._client.__aenter__()  # type: ignore[no-untyped-call]
                    logger.info("Connected with OAuth fallback")
                except Exception:  # noqa: BLE001
                    raise first_error from None
            else:
                raise

        return self

    async def __aexit__(self, *args: object) -> None:
        """Exit context manager and cleanup."""
        try:
            await self._client.__aexit__(None, None, None)  # type: ignore[no-untyped-call]
        except Exception as e:  # noqa: BLE001
            logger.warning("Error during FastMCP client cleanup", error=e)

    def get_resource_fs(self) -> MCPFileSystem:
        """Get a filesystem for accessing MCP resources."""
        from upathtools.filesystems import MCPFileSystem

        return MCPFileSystem(client=self._client)

    def get_tools_fs(self) -> MCPToolsFileSystem:
        """Get a filesystem for accessing MCP tools as code."""
        from upathtools.filesystems import MCPToolsFileSystem

        return MCPToolsFileSystem(client=self._client)

    async def _log_handler(self, message: LogMessage) -> None:
        """Handle server log messages."""
        level = MCP_TO_LOGGING.get(message.level, logging.INFO)
        logger.log(level, "MCP Server: ", data=message.data)

    async def _forwarding_elicitation_callback[T](
        self,
        message: str,
        response_type: type[T],
        params: ElicitRequestParams,
        context: RequestContext[Any, Any],
    ) -> T | dict[str, Any] | Any:
        """Forwarding callback that delegates to current handler.

        This callback is registered once at connection time, but delegates to
        _current_elicitation_handler which can be swapped per tool call.
        """
        from fastmcp.client.elicitation import ElicitResult

        # Try current handler first (set per call_tool)
        if self._current_elicitation_handler:
            return await self._current_elicitation_handler(message, response_type, params, context)
        # No handler available - decline by default
        return ElicitResult(action="decline")

    def _get_client(
        self, config: MCPServerConfig, force_oauth: bool = False
    ) -> fastmcp.Client[Any]:
        """Create FastMCP client based on config."""
        import fastmcp
        from fastmcp.client import SSETransport, StreamableHttpTransport
        from fastmcp.client.transports import StdioTransport

        transport: ClientTransport
        # Create transport based on config type
        match config:
            case StdioMCPServerConfig(command=command, args=args):
                env = config.get_env_vars()
                transport = StdioTransport(command=command, args=args, env=env)
                oauth = False
                if force_oauth:
                    msg = "OAuth is not supported for StdioMCPServerConfig"
                    raise ValueError(msg)

            case SSEMCPServerConfig(url=url, headers=headers, auth=auth):
                transport = SSETransport(url=url, headers=headers)
                oauth = auth.oauth

            case StreamableHTTPMCPServerConfig(url=url, headers=headers, auth=auth):
                transport = StreamableHttpTransport(url=url, headers=headers)
                oauth = auth.oauth
            case _ as unreachable:
                assert_never(unreachable)

        # Create message handler if needed
        msg_handler = self._message_handler or MCPMessageHandler(
            self,
            self._tool_change_callback,
            self._prompt_change_callback,
            self._resource_change_callback,
        )
        return fastmcp.Client(
            transport,
            log_handler=self._log_handler,
            roots=self._accessible_roots,
            timeout=config.timeout,
            elicitation_handler=self._forwarding_elicitation_callback,
            sampling_handler=self._sampling_callback,
            message_handler=msg_handler,
            auth="oauth" if (force_oauth or oauth) else None,
        )

    async def list_tools(self) -> list[MCPTool]:
        """Get available tools directly from the server."""
        if not self.connected:
            msg = "Not connected to MCP server"
            raise RuntimeError(msg)

        try:
            tools = await self._client.list_tools()
            logger.debug("Listed tools from MCP server", num_tools=len(tools))
        except Exception as e:  # noqa: BLE001
            logger.warning("Failed to list tools", error=e)
            return []
        else:
            return tools

    async def list_prompts(self) -> list[MCPPrompt]:
        """Get available prompts from the server."""
        if not self.connected:
            msg = "Not connected to MCP server"
            raise RuntimeError(msg)

        try:
            return await self._client.list_prompts()
        except Exception as e:  # noqa: BLE001
            logger.debug("Failed to list prompts", error=e)
            return []

    async def list_resources(self) -> list[MCPResource]:
        """Get available resources from the server."""
        if not self.connected:
            msg = "Not connected to MCP server"
            raise RuntimeError(msg)

        try:
            return await self._client.list_resources()
        except Exception as e:
            msg = f"Failed to list resources: {e}"
            raise RuntimeError(msg) from e

    async def get_prompt(
        self, name: str, arguments: dict[str, str] | None = None
    ) -> GetPromptResult:
        """Get a specific prompt's content."""
        if not self.connected:
            msg = "Not connected to MCP server"
            raise RuntimeError(msg)

        try:
            return await self._client.get_prompt_mcp(name, arguments)
        except Exception as e:
            msg = f"Failed to get prompt {name!r}: {e}"
            raise RuntimeError(msg) from e

    def convert_tool(self, tool: MCPTool) -> Tool:
        """Create a properly typed callable from MCP tool schema."""

        async def tool_callable(
            ctx: RunContext, agent_ctx: AgentContext[Any], **kwargs: Any
        ) -> str | Any | ToolReturn:
            """Dynamically generated MCP tool wrapper."""
            # Filter out None values for optional params
            schema_props = tool.inputSchema.get("properties", {})
            required_props = set(tool.inputSchema.get("required", []))
            filtered_kwargs = {
                k: v
                for k, v in kwargs.items()
                if k in required_props or (k in schema_props and v is not None)
            }
            return await self.call_tool(tool.name, ctx, filtered_kwargs, agent_ctx)

        # Set proper signature and annotations with both RunContext and AgentContext
        schema = mcp_tool_to_fn_schema(tool)
        fn_schema = FunctionSchema.from_dict(schema)
        sig = fn_schema.to_python_signature()

        tool_callable.__signature__ = create_modified_signature(  # type: ignore[attr-defined]
            sig, inject={"ctx": RunContext, "agent_ctx": AgentContext}
        )
        annotations = fn_schema.get_annotations()
        annotations["ctx"] = RunContext
        annotations["agent_ctx"] = AgentContext
        # Update return annotation to support multiple types
        annotations["return"] = str | Any | ToolReturn  # type: ignore
        tool_callable.__annotations__ = annotations
        tool_callable.__name__ = tool.name
        tool_callable.__doc__ = tool.description or "No description provided."
        return Tool.from_callable(tool_callable, source="mcp")

    async def call_tool(
        self,
        name: str,
        run_context: RunContext,
        arguments: dict[str, Any] | None = None,
        agent_ctx: AgentContext[Any] | None = None,
    ) -> ToolReturn | str | Any:
        """Call an MCP tool with full PydanticAI return type support."""
        if not self.connected:
            msg = "Not connected to MCP server"
            raise RuntimeError(msg)

        # Create progress handler that bridges to AgentContext if available
        progress_handler = None
        if agent_ctx:

            async def fastmcp_progress_handler(
                progress: float,
                total: float | None,
                message: str | None,
            ) -> None:
                await agent_ctx.report_progress(progress, total, message or "")

            progress_handler = fastmcp_progress_handler

        # Set up per-call elicitation handler from AgentContext
        if agent_ctx:

            async def elicitation_handler[T](
                message: str,
                response_type: type[T],
                params: ElicitRequestParams,
                context: RequestContext[Any, Any],
            ) -> T | dict[str, Any] | Any:
                from fastmcp.client.elicitation import ElicitResult
                from mcp.types import ElicitResult as MCPElicitResult, ErrorData

                result = await agent_ctx.handle_elicitation(params)
                match result:
                    case MCPElicitResult(action="accept", content=content):
                        return content
                    case MCPElicitResult(action="cancel"):
                        return ElicitResult(action="cancel")
                    case MCPElicitResult(action="decline"):
                        return ElicitResult(action="decline")
                    case ErrorData():
                        return ElicitResult(action="decline")
                    case _:
                        return ElicitResult(action="decline")

            self._current_elicitation_handler = elicitation_handler

        try:
            result = await self._client.call_tool(
                name, arguments, progress_handler=progress_handler
            )
            content = await self._convert_mcp_content(result.content)
            # Decision logic for return type
            match (result.data is not None, bool(content)):
                case (True, True):  # Both structured data and rich content -> ToolReturn
                    return ToolReturn(return_value=result.data, content=content)
                case (True, False):  # Only structured data -> return directly
                    return result.data
                case (False, True):  # Only content -> ToolReturn with content
                    msg = "Tool executed successfully"
                    return ToolReturn(return_value=msg, content=content)
                case (False, False):  # Fallback to text extraction
                    return extract_text_content(result.content)
                case _:  # Handle unexpected cases
                    msg = f"Unexpected MCP content: {result.content}"
                    raise ValueError(msg)  # noqa: TRY301
        except Exception as e:
            msg = f"MCP tool call failed: {e}"
            raise RuntimeError(msg) from e
        finally:
            # Clear per-call handler
            self._current_elicitation_handler = None

    async def _convert_mcp_content(
        self,
        mcp_content: Sequence[ContentBlock | TextResourceContents | BlobResourceContents],
    ) -> list[str | BinaryContent]:
        """Convert MCP content blocks to PydanticAI content types."""
        from llmling_agent.mcp_server.conversions import convert_mcp_content

        return await convert_mcp_content(mcp_content)

connected property

connected: bool

Check if client is connected by examining session state.

__aenter__ async

__aenter__() -> Self

Enter context manager.

Source code in src/llmling_agent/mcp_server/client.py

async def __aenter__(self) -> Self:
    """Enter context manager."""
    try:
        # First attempt with configured auth
        await self._client.__aenter__()  # type: ignore[no-untyped-call]

    except Exception as first_error:
        # OAuth fallback for HTTP/SSE if not already using OAuth
        if not isinstance(self.config, StdioMCPServerConfig) and not self.config.auth.oauth:
            try:
                with contextlib.suppress(Exception):
                    await self._client.__aexit__(None, None, None)  # type: ignore[no-untyped-call]
                self._client = self._get_client(self.config, force_oauth=True)
                await self._client.__aenter__()  # type: ignore[no-untyped-call]
                logger.info("Connected with OAuth fallback")
            except Exception:  # noqa: BLE001
                raise first_error from None
        else:
            raise

    return self

__aexit__ async

__aexit__(*args: object) -> None

Exit context manager and cleanup.

Source code in src/llmling_agent/mcp_server/client.py

async def __aexit__(self, *args: object) -> None:
    """Exit context manager and cleanup."""
    try:
        await self._client.__aexit__(None, None, None)  # type: ignore[no-untyped-call]
    except Exception as e:  # noqa: BLE001
        logger.warning("Error during FastMCP client cleanup", error=e)

call_tool async

call_tool(
    name: str,
    run_context: RunContext,
    arguments: dict[str, Any] | None = None,
    agent_ctx: AgentContext[Any] | None = None,
) -> ToolReturn | str | Any

Call an MCP tool with full PydanticAI return type support.

Source code in src/llmling_agent/mcp_server/client.py

async def call_tool(
    self,
    name: str,
    run_context: RunContext,
    arguments: dict[str, Any] | None = None,
    agent_ctx: AgentContext[Any] | None = None,
) -> ToolReturn | str | Any:
    """Call an MCP tool with full PydanticAI return type support."""
    if not self.connected:
        msg = "Not connected to MCP server"
        raise RuntimeError(msg)

    # Create progress handler that bridges to AgentContext if available
    progress_handler = None
    if agent_ctx:

        async def fastmcp_progress_handler(
            progress: float,
            total: float | None,
            message: str | None,
        ) -> None:
            await agent_ctx.report_progress(progress, total, message or "")

        progress_handler = fastmcp_progress_handler

    # Set up per-call elicitation handler from AgentContext
    if agent_ctx:

        async def elicitation_handler[T](
            message: str,
            response_type: type[T],
            params: ElicitRequestParams,
            context: RequestContext[Any, Any],
        ) -> T | dict[str, Any] | Any:
            from fastmcp.client.elicitation import ElicitResult
            from mcp.types import ElicitResult as MCPElicitResult, ErrorData

            result = await agent_ctx.handle_elicitation(params)
            match result:
                case MCPElicitResult(action="accept", content=content):
                    return content
                case MCPElicitResult(action="cancel"):
                    return ElicitResult(action="cancel")
                case MCPElicitResult(action="decline"):
                    return ElicitResult(action="decline")
                case ErrorData():
                    return ElicitResult(action="decline")
                case _:
                    return ElicitResult(action="decline")

        self._current_elicitation_handler = elicitation_handler

    try:
        result = await self._client.call_tool(
            name, arguments, progress_handler=progress_handler
        )
        content = await self._convert_mcp_content(result.content)
        # Decision logic for return type
        match (result.data is not None, bool(content)):
            case (True, True):  # Both structured data and rich content -> ToolReturn
                return ToolReturn(return_value=result.data, content=content)
            case (True, False):  # Only structured data -> return directly
                return result.data
            case (False, True):  # Only content -> ToolReturn with content
                msg = "Tool executed successfully"
                return ToolReturn(return_value=msg, content=content)
            case (False, False):  # Fallback to text extraction
                return extract_text_content(result.content)
            case _:  # Handle unexpected cases
                msg = f"Unexpected MCP content: {result.content}"
                raise ValueError(msg)  # noqa: TRY301
    except Exception as e:
        msg = f"MCP tool call failed: {e}"
        raise RuntimeError(msg) from e
    finally:
        # Clear per-call handler
        self._current_elicitation_handler = None

convert_tool

convert_tool(tool: Tool) -> Tool

Create a properly typed callable from MCP tool schema.

Source code in src/llmling_agent/mcp_server/client.py

def convert_tool(self, tool: MCPTool) -> Tool:
    """Create a properly typed callable from MCP tool schema."""

    async def tool_callable(
        ctx: RunContext, agent_ctx: AgentContext[Any], **kwargs: Any
    ) -> str | Any | ToolReturn:
        """Dynamically generated MCP tool wrapper."""
        # Filter out None values for optional params
        schema_props = tool.inputSchema.get("properties", {})
        required_props = set(tool.inputSchema.get("required", []))
        filtered_kwargs = {
            k: v
            for k, v in kwargs.items()
            if k in required_props or (k in schema_props and v is not None)
        }
        return await self.call_tool(tool.name, ctx, filtered_kwargs, agent_ctx)

    # Set proper signature and annotations with both RunContext and AgentContext
    schema = mcp_tool_to_fn_schema(tool)
    fn_schema = FunctionSchema.from_dict(schema)
    sig = fn_schema.to_python_signature()

    tool_callable.__signature__ = create_modified_signature(  # type: ignore[attr-defined]
        sig, inject={"ctx": RunContext, "agent_ctx": AgentContext}
    )
    annotations = fn_schema.get_annotations()
    annotations["ctx"] = RunContext
    annotations["agent_ctx"] = AgentContext
    # Update return annotation to support multiple types
    annotations["return"] = str | Any | ToolReturn  # type: ignore
    tool_callable.__annotations__ = annotations
    tool_callable.__name__ = tool.name
    tool_callable.__doc__ = tool.description or "No description provided."
    return Tool.from_callable(tool_callable, source="mcp")

get_prompt async

get_prompt(name: str, arguments: dict[str, str] | None = None) -> GetPromptResult

Get a specific prompt's content.

Source code in src/llmling_agent/mcp_server/client.py

async def get_prompt(
    self, name: str, arguments: dict[str, str] | None = None
) -> GetPromptResult:
    """Get a specific prompt's content."""
    if not self.connected:
        msg = "Not connected to MCP server"
        raise RuntimeError(msg)

    try:
        return await self._client.get_prompt_mcp(name, arguments)
    except Exception as e:
        msg = f"Failed to get prompt {name!r}: {e}"
        raise RuntimeError(msg) from e

get_resource_fs

get_resource_fs() -> MCPFileSystem

Get a filesystem for accessing MCP resources.

Source code in src/llmling_agent/mcp_server/client.py

def get_resource_fs(self) -> MCPFileSystem:
    """Get a filesystem for accessing MCP resources."""
    from upathtools.filesystems import MCPFileSystem

    return MCPFileSystem(client=self._client)

get_tools_fs

get_tools_fs() -> MCPToolsFileSystem

Get a filesystem for accessing MCP tools as code.

Source code in src/llmling_agent/mcp_server/client.py

def get_tools_fs(self) -> MCPToolsFileSystem:
    """Get a filesystem for accessing MCP tools as code."""
    from upathtools.filesystems import MCPToolsFileSystem

    return MCPToolsFileSystem(client=self._client)

list_prompts async

list_prompts() -> list[Prompt]

Get available prompts from the server.

Source code in src/llmling_agent/mcp_server/client.py

async def list_prompts(self) -> list[MCPPrompt]:
    """Get available prompts from the server."""
    if not self.connected:
        msg = "Not connected to MCP server"
        raise RuntimeError(msg)

    try:
        return await self._client.list_prompts()
    except Exception as e:  # noqa: BLE001
        logger.debug("Failed to list prompts", error=e)
        return []

list_resources async

list_resources() -> list[Resource]

Get available resources from the server.

Source code in src/llmling_agent/mcp_server/client.py

async def list_resources(self) -> list[MCPResource]:
    """Get available resources from the server."""
    if not self.connected:
        msg = "Not connected to MCP server"
        raise RuntimeError(msg)

    try:
        return await self._client.list_resources()
    except Exception as e:
        msg = f"Failed to list resources: {e}"
        raise RuntimeError(msg) from e

list_tools async

list_tools() -> list[Tool]

Get available tools directly from the server.

Source code in src/llmling_agent/mcp_server/client.py

async def list_tools(self) -> list[MCPTool]:
    """Get available tools directly from the server."""
    if not self.connected:
        msg = "Not connected to MCP server"
        raise RuntimeError(msg)

    try:
        tools = await self._client.list_tools()
        logger.debug("Listed tools from MCP server", num_tools=len(tools))
    except Exception as e:  # noqa: BLE001
        logger.warning("Failed to list tools", error=e)
        return []
    else:
        return tools

ToolBridgeRegistry

Registry for managing multiple tool bridges.

Useful when multiple ACP agents need access to different toolsets.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

class ToolBridgeRegistry:
    """Registry for managing multiple tool bridges.

    Useful when multiple ACP agents need access to different toolsets.
    """

    def __init__(self) -> None:
        self._bridges: dict[str, ToolManagerBridge] = {}
        self._port_counter = 18000  # Start port range for auto-allocation

    async def create_bridge(
        self,
        name: str,
        tool_manager: ToolManager,
        pool: AgentPool[Any],
        *,
        owner_agent_name: str | None = None,
        input_provider: InputProvider | None = None,
    ) -> ToolManagerBridge:
        """Create and register a new bridge.

        Args:
            name: Unique name for this bridge
            tool_manager: ToolManager to expose
            pool: Agent pool for context
            owner_agent_name: Optional owner agent name
            input_provider: Optional input provider

        Returns:
            Started ToolManagerBridge
        """
        if name in self._bridges:
            msg = f"Bridge {name!r} already exists"
            raise ValueError(msg)

        config = BridgeConfig(port=self._port_counter, server_name=f"llmling-{name}")
        self._port_counter += 1

        bridge = ToolManagerBridge(
            tool_manager=tool_manager,
            pool=pool,
            config=config,
            owner_agent_name=owner_agent_name,
            input_provider=input_provider,
        )
        await bridge.start()
        self._bridges[name] = bridge
        return bridge

    async def get_bridge(self, name: str) -> ToolManagerBridge:
        """Get a bridge by name."""
        if name not in self._bridges:
            msg = f"Bridge {name!r} not found"
            raise KeyError(msg)
        return self._bridges[name]

    async def remove_bridge(self, name: str) -> None:
        """Stop and remove a bridge."""
        if name in self._bridges:
            await self._bridges[name].stop()
            del self._bridges[name]

    async def close_all(self) -> None:
        """Stop all bridges."""
        for bridge in list(self._bridges.values()):
            await bridge.stop()
        self._bridges.clear()

    def get_all_mcp_configs(self) -> list[HttpMcpServer | SseMcpServer]:
        """Get MCP server configs for all active bridges."""
        return [bridge.get_mcp_server_config() for bridge in self._bridges.values()]

close_all async

close_all() -> None

Stop all bridges.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def close_all(self) -> None:
    """Stop all bridges."""
    for bridge in list(self._bridges.values()):
        await bridge.stop()
    self._bridges.clear()

create_bridge async

create_bridge(
    name: str,
    tool_manager: ToolManager,
    pool: AgentPool[Any],
    *,
    owner_agent_name: str | None = None,
    input_provider: InputProvider | None = None
) -> ToolManagerBridge

Create and register a new bridge.

Parameters:

Name	Type	Description	Default
name	str	Unique name for this bridge	required
tool_manager	ToolManager	ToolManager to expose	required
pool	AgentPool[Any]	Agent pool for context	required
owner_agent_name	str | None	Optional owner agent name	None
input_provider	InputProvider | None	Optional input provider	None

Returns:

Type	Description
ToolManagerBridge	Started ToolManagerBridge

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def create_bridge(
    self,
    name: str,
    tool_manager: ToolManager,
    pool: AgentPool[Any],
    *,
    owner_agent_name: str | None = None,
    input_provider: InputProvider | None = None,
) -> ToolManagerBridge:
    """Create and register a new bridge.

    Args:
        name: Unique name for this bridge
        tool_manager: ToolManager to expose
        pool: Agent pool for context
        owner_agent_name: Optional owner agent name
        input_provider: Optional input provider

    Returns:
        Started ToolManagerBridge
    """
    if name in self._bridges:
        msg = f"Bridge {name!r} already exists"
        raise ValueError(msg)

    config = BridgeConfig(port=self._port_counter, server_name=f"llmling-{name}")
    self._port_counter += 1

    bridge = ToolManagerBridge(
        tool_manager=tool_manager,
        pool=pool,
        config=config,
        owner_agent_name=owner_agent_name,
        input_provider=input_provider,
    )
    await bridge.start()
    self._bridges[name] = bridge
    return bridge

get_all_mcp_configs

get_all_mcp_configs() -> list[HttpMcpServer | SseMcpServer]

Get MCP server configs for all active bridges.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

def get_all_mcp_configs(self) -> list[HttpMcpServer | SseMcpServer]:
    """Get MCP server configs for all active bridges."""
    return [bridge.get_mcp_server_config() for bridge in self._bridges.values()]

get_bridge async

get_bridge(name: str) -> ToolManagerBridge

Get a bridge by name.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def get_bridge(self, name: str) -> ToolManagerBridge:
    """Get a bridge by name."""
    if name not in self._bridges:
        msg = f"Bridge {name!r} not found"
        raise KeyError(msg)
    return self._bridges[name]

remove_bridge async

remove_bridge(name: str) -> None

Stop and remove a bridge.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def remove_bridge(self, name: str) -> None:
    """Stop and remove a bridge."""
    if name in self._bridges:
        await self._bridges[name].stop()
        del self._bridges[name]

ToolManagerBridge dataclass

Exposes a ToolManager's tools as an MCP server for ACP agents.

This bridge allows external ACP agents to access our internal toolsets (SubagentTools, AgentManagementTools, etc.) via HTTP MCP transport.

The bridge creates synthetic AgentContext instances for tool invocations, allowing tools that need pool access to work correctly.

Example

async with AgentPool() as pool:
    agent = pool.agents["my_agent"]
    bridge = ToolManagerBridge(
        tool_manager=agent.tools,
        pool=pool,
        config=BridgeConfig(port=8765),
    )
    async with bridge:
        # Bridge is running, get MCP config for ACP agent
        mcp_config = bridge.get_mcp_server_config()
        # Pass to ACP agent...

Source code in src/llmling_agent/mcp_server/tool_bridge.py

@dataclass
class ToolManagerBridge:
    """Exposes a ToolManager's tools as an MCP server for ACP agents.

    This bridge allows external ACP agents to access our internal toolsets
    (SubagentTools, AgentManagementTools, etc.) via HTTP MCP transport.

    The bridge creates synthetic AgentContext instances for tool invocations,
    allowing tools that need pool access to work correctly.

    Example:
        ```python
        async with AgentPool() as pool:
            agent = pool.agents["my_agent"]
            bridge = ToolManagerBridge(
                tool_manager=agent.tools,
                pool=pool,
                config=BridgeConfig(port=8765),
            )
            async with bridge:
                # Bridge is running, get MCP config for ACP agent
                mcp_config = bridge.get_mcp_server_config()
                # Pass to ACP agent...
        ```
    """

    tool_manager: ToolManager
    """The ToolManager whose tools to expose."""

    pool: AgentPool[Any]
    """Agent pool for context creation."""

    config: BridgeConfig = field(default_factory=BridgeConfig)
    """Bridge configuration."""

    owner_agent_name: str | None = None
    """Name of the agent that owns this bridge (for context creation)."""

    input_provider: InputProvider | None = None
    """Optional input provider for tool confirmations."""

    _mcp: FastMCP | None = field(default=None, init=False, repr=False)
    """FastMCP server instance."""

    _server: Server | None = field(default=None, init=False, repr=False)
    """Uvicorn server instance."""

    _server_task: asyncio.Task[None] | None = field(default=None, init=False, repr=False)
    """Background task running the server."""

    _actual_port: int | None = field(default=None, init=False, repr=False)
    """Actual port the server is bound to."""

    async def __aenter__(self) -> Self:
        """Start the MCP server."""
        await self.start()
        return self

    async def __aexit__(self, *args: object) -> None:
        """Stop the MCP server."""
        await self.stop()

    async def start(self) -> None:
        """Start the HTTP MCP server in the background."""
        self._mcp = FastMCP(name=self.config.server_name)
        await self._register_tools()
        await self._start_server()

    async def stop(self) -> None:
        """Stop the HTTP MCP server."""
        if self._server:
            self._server.should_exit = True
            if self._server_task:
                try:
                    await asyncio.wait_for(self._server_task, timeout=5.0)
                except TimeoutError:
                    self._server_task.cancel()
                    with suppress(asyncio.CancelledError):
                        await self._server_task
            self._server = None
            self._server_task = None
        self._mcp = None
        self._actual_port = None
        logger.info("ToolManagerBridge stopped")

    @property
    def port(self) -> int:
        """Get the actual port the server is running on."""
        if self._actual_port is None:
            msg = "Server not started"
            raise RuntimeError(msg)
        return self._actual_port

    @property
    def url(self) -> str:
        """Get the server URL."""
        path = "/sse" if self.config.transport == "sse" else "/mcp"
        return f"http://{self.config.host}:{self.port}{path}"

    def get_mcp_server_config(self) -> HttpMcpServer | SseMcpServer:
        """Get ACP-compatible MCP server configuration.

        Returns config suitable for passing to ACP agent's NewSessionRequest.
        """
        from acp.schema.mcp import HttpMcpServer, SseMcpServer

        url = HttpUrl(self.url)
        if self.config.transport == "sse":
            return SseMcpServer(name=self.config.server_name, url=url, headers=[])
        return HttpMcpServer(name=self.config.server_name, url=url, headers=[])

    def _create_proxy_context(
        self,
        tool_name: str,
        tool_call_id: str,
        tool_input: dict[str, Any],
        mcp_ctx: Context,
    ) -> AgentContext[None]:
        """Create a synthetic AgentContext for MCP tool invocation.

        This context provides pool access for delegation tools while
        bridging progress reporting to MCP.
        """
        from llmling_agent.agent.context import AgentContext
        from llmling_agent.models.agents import AgentConfig
        from llmling_agent.models.manifest import AgentsManifest

        # Use owner agent's config or create minimal one
        agent_config: AgentConfig
        definition: AgentsManifest
        if self.owner_agent_name and self.owner_agent_name in self.pool.agents:
            agent = self.pool.agents[self.owner_agent_name]
            agent_config = agent.context.config
            definition = agent.context.definition
        else:
            # Create minimal config for bridge-only usage
            agent_config = AgentConfig(name="bridge")
            definition = AgentsManifest()

        return AgentContext(
            node_name=self.owner_agent_name or "bridge",
            pool=self.pool,
            config=agent_config,
            definition=definition,
            input_provider=self.input_provider,
            data=None,
            tool_name=tool_name,
            tool_call_id=tool_call_id,
            tool_input=tool_input,
        )

    async def _register_tools(self) -> None:
        """Register all ToolManager tools with the FastMCP server."""
        if not self._mcp:
            return

        tools = await self.tool_manager.get_tools(state="enabled")
        for tool in tools:
            self._register_single_tool(tool)
        msg = "Registered tools with MCP bridge"
        logger.info(msg, tool_count=len(tools), tools=[t.name for t in tools])

    def _register_single_tool(self, tool: Tool) -> None:
        """Register a single tool with the FastMCP server."""
        if not self._mcp:
            return

        # Create a custom FastMCP Tool that wraps our tool
        bridge_tool = _BridgeTool(tool=tool, bridge=self)
        self._mcp.add_tool(bridge_tool)

    async def invoke_tool_with_context(
        self,
        tool: Tool,
        agent_ctx: AgentContext[None],
        kwargs: dict[str, Any],
    ) -> Any:
        """Invoke a tool with proper context injection.

        Handles tools that expect AgentContext, RunContext, or neither.
        """
        from llmling_agent.agent.context import AgentContext as AgentContextType

        fn = tool.callable
        sig = inspect.signature(fn)

        # Check what context types the tool expects
        needs_agent_ctx = any(
            param.annotation is AgentContextType
            or (
                hasattr(param.annotation, "__origin__")
                and param.annotation.__origin__ is AgentContextType
            )
            or str(param.annotation).startswith("AgentContext")
            for param in sig.parameters.values()
        )

        # Find parameter name for AgentContext if needed
        agent_ctx_param: str | None = None
        if needs_agent_ctx:
            for name, param in sig.parameters.items():
                annotation = param.annotation
                if annotation is AgentContextType or str(annotation).startswith("AgentContext"):
                    agent_ctx_param = name
                    break

        # Invoke with appropriate context injection
        if agent_ctx_param:
            kwargs[agent_ctx_param] = agent_ctx

        # Execute the tool
        result = fn(**kwargs)
        if inspect.isawaitable(result):
            result = await result

        return result

    async def _start_server(self) -> None:
        """Start the uvicorn server in the background."""
        import socket

        import uvicorn

        if not self._mcp:
            msg = "MCP server not initialized"
            raise RuntimeError(msg)

        # Determine actual port (auto-select if 0)
        port = self.config.port
        if port == 0:
            with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
                s.bind((self.config.host, 0))
                port = s.getsockname()[1]
        self._actual_port = port
        # Create the ASGI app
        app = self._mcp.http_app(transport=self.config.transport)  # type: ignore[arg-type]
        # Configure uvicorn
        cfg = uvicorn.Config(app=app, host=self.config.host, port=port, log_level="warning")
        self._server = uvicorn.Server(cfg)
        # Start server in background task
        name = f"mcp-bridge-{self.config.server_name}"
        self._server_task = asyncio.create_task(self._server.serve(), name=name)
        await asyncio.sleep(0.1)  # Wait briefly for server to start
        msg = "ToolManagerBridge started"
        logger.info(msg, url=self.url, transport=self.config.transport)

config class-attribute instance-attribute

config: BridgeConfig = field(default_factory=BridgeConfig)

Bridge configuration.

input_provider class-attribute instance-attribute

input_provider: InputProvider | None = None

Optional input provider for tool confirmations.

owner_agent_name class-attribute instance-attribute

owner_agent_name: str | None = None

Name of the agent that owns this bridge (for context creation).

pool instance-attribute

pool: AgentPool[Any]

Agent pool for context creation.

port property

port: int

Get the actual port the server is running on.

tool_manager instance-attribute

tool_manager: ToolManager

The ToolManager whose tools to expose.

url property

url: str

Get the server URL.

__aenter__ async

__aenter__() -> Self

Start the MCP server.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def __aenter__(self) -> Self:
    """Start the MCP server."""
    await self.start()
    return self

__aexit__ async

__aexit__(*args: object) -> None

Stop the MCP server.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def __aexit__(self, *args: object) -> None:
    """Stop the MCP server."""
    await self.stop()

get_mcp_server_config

get_mcp_server_config() -> HttpMcpServer | SseMcpServer

Get ACP-compatible MCP server configuration.

Returns config suitable for passing to ACP agent's NewSessionRequest.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

def get_mcp_server_config(self) -> HttpMcpServer | SseMcpServer:
    """Get ACP-compatible MCP server configuration.

    Returns config suitable for passing to ACP agent's NewSessionRequest.
    """
    from acp.schema.mcp import HttpMcpServer, SseMcpServer

    url = HttpUrl(self.url)
    if self.config.transport == "sse":
        return SseMcpServer(name=self.config.server_name, url=url, headers=[])
    return HttpMcpServer(name=self.config.server_name, url=url, headers=[])

invoke_tool_with_context async

invoke_tool_with_context(tool: Tool, agent_ctx: AgentContext[None], kwargs: dict[str, Any]) -> Any

Invoke a tool with proper context injection.

Handles tools that expect AgentContext, RunContext, or neither.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def invoke_tool_with_context(
    self,
    tool: Tool,
    agent_ctx: AgentContext[None],
    kwargs: dict[str, Any],
) -> Any:
    """Invoke a tool with proper context injection.

    Handles tools that expect AgentContext, RunContext, or neither.
    """
    from llmling_agent.agent.context import AgentContext as AgentContextType

    fn = tool.callable
    sig = inspect.signature(fn)

    # Check what context types the tool expects
    needs_agent_ctx = any(
        param.annotation is AgentContextType
        or (
            hasattr(param.annotation, "__origin__")
            and param.annotation.__origin__ is AgentContextType
        )
        or str(param.annotation).startswith("AgentContext")
        for param in sig.parameters.values()
    )

    # Find parameter name for AgentContext if needed
    agent_ctx_param: str | None = None
    if needs_agent_ctx:
        for name, param in sig.parameters.items():
            annotation = param.annotation
            if annotation is AgentContextType or str(annotation).startswith("AgentContext"):
                agent_ctx_param = name
                break

    # Invoke with appropriate context injection
    if agent_ctx_param:
        kwargs[agent_ctx_param] = agent_ctx

    # Execute the tool
    result = fn(**kwargs)
    if inspect.isawaitable(result):
        result = await result

    return result

start async

start() -> None

Start the HTTP MCP server in the background.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def start(self) -> None:
    """Start the HTTP MCP server in the background."""
    self._mcp = FastMCP(name=self.config.server_name)
    await self._register_tools()
    await self._start_server()

stop async

stop() -> None

Stop the HTTP MCP server.

Source code in src/llmling_agent/mcp_server/tool_bridge.py

async def stop(self) -> None:
    """Stop the HTTP MCP server."""
    if self._server:
        self._server.should_exit = True
        if self._server_task:
            try:
                await asyncio.wait_for(self._server_task, timeout=5.0)
            except TimeoutError:
                self._server_task.cancel()
                with suppress(asyncio.CancelledError):
                    await self._server_task
        self._server = None
        self._server_task = None
    self._mcp = None
    self._actual_port = None
    logger.info("ToolManagerBridge stopped")

create_tool_bridge async

create_tool_bridge(
    tool_manager: ToolManager,
    pool: AgentPool[Any],
    *,
    host: str = "127.0.0.1",
    port: int = 0,
    transport: str = "sse",
    owner_agent_name: str | None = None,
    input_provider: InputProvider | None = None
) -> AsyncIterator[ToolManagerBridge]

Create and start a ToolManagerBridge as a context manager.

Parameters:

Name	Type	Description	Default
tool_manager	ToolManager	ToolManager whose tools to expose	required
pool	AgentPool[Any]	Agent pool for context creation	required
host	str	Host to bind to	'127.0.0.1'
port	int	Port to bind to (0 = auto-select)	0
transport	str	Transport protocol ('sse' or 'streamable-http')	'sse'
owner_agent_name	str | None	Name of owning agent for context	None
input_provider	InputProvider | None	Optional input provider	None

Yields:

Type	Description
AsyncIterator[ToolManagerBridge]	Running ToolManagerBridge instance

Source code in src/llmling_agent/mcp_server/tool_bridge.py

@asynccontextmanager
async def create_tool_bridge(
    tool_manager: ToolManager,
    pool: AgentPool[Any],
    *,
    host: str = "127.0.0.1",
    port: int = 0,
    transport: str = "sse",
    owner_agent_name: str | None = None,
    input_provider: InputProvider | None = None,
) -> AsyncIterator[ToolManagerBridge]:
    """Create and start a ToolManagerBridge as a context manager.

    Args:
        tool_manager: ToolManager whose tools to expose
        pool: Agent pool for context creation
        host: Host to bind to
        port: Port to bind to (0 = auto-select)
        transport: Transport protocol ('sse' or 'streamable-http')
        owner_agent_name: Name of owning agent for context
        input_provider: Optional input provider

    Yields:
        Running ToolManagerBridge instance
    """
    config = BridgeConfig(host=host, port=port, transport=transport)
    bridge = ToolManagerBridge(
        tool_manager=tool_manager,
        pool=pool,
        config=config,
        owner_agent_name=owner_agent_name,
        input_provider=input_provider,
    )
    async with bridge:
        yield bridge