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MCP tools loader for Axio

Project description

axio-tools-mcp

PyPI Python License: MIT

Model Context Protocol (MCP) bridge for axio.

Connect any MCP server to your axio agent. Tools exposed by MCP servers are discovered at runtime and become first-class axio Tool instances — no manual wiring required.

Features

  • Dynamic tool discovery — connects to MCP servers and converts their tools into axio Tool instances automatically
  • Multiple servers — configure and run several MCP servers simultaneously
  • Lifecycle management — handles server startup, shutdown, and reconnection
  • TUI integration — ships a settings screen for managing MCP server configuration from within axio-tui

Installation

pip install axio-tools-mcp

Usage

With axio-tui (recommended)

pip install "axio-tui[mcp]"
uv run axio   # MCP Servers section appears in settings

Standalone

import asyncio
from axio_tools_mcp.registry import MCPRegistry
from axio.agent import Agent
from axio.context import MemoryContextStore

async def main() -> None:
    registry = MCPRegistry()
    await registry.init(config=None)

    tools = registry.all_tools   # list[axio.Tool]
    print(f"Loaded {len(tools)} tools from MCP servers")

    # Pass any CompletionTransport — e.g. OpenAITransport, AnthropicTransport
    agent = Agent(
        system="You are a helpful assistant.",
        tools=tools,
        transport=transport,
    )
    result = await agent.run("Use the available tools to help me", MemoryContextStore())
    print(result)

    await registry.close()

asyncio.run(main())

Transport types

Two transport types are supported, selected by which field is set in the server config:

Transport Config field Protocol
stdio command Spawns a subprocess; communicates over stdin/stdout (MCP stdio transport)
HTTP url Connects to a running HTTP server using the MCP Streamable HTTP transport (httpx)

Exactly one of command or url must be set per server — providing both or neither raises a ValueError.

For stdio servers, stderr output from the subprocess is forwarded to the Python logger as warnings under the mcp:<server-name> prefix.

HTTP servers accept optional headers (e.g., for bearer tokens) and a configurable timeout (default: 30 seconds).

Tool naming

Tools from MCP servers are named using the pattern <server_name>__<tool_name>. For example, a server named filesystem that exposes a tool called read_file becomes filesystem__read_file in axio. The tool description is taken from the MCP tool's description field, falling back to the tool name if no description is provided.

Error handling

When an MCP server fails to connect or start, the error is logged at ERROR level and the server is skipped — no exception is raised to the caller. registry.all_tools will simply not include any tools from the failed server. The error message is accessible via registry.server_status(name) (returns "error") and the raw error string is stored internally.

Lifecycle: close()

Call await registry.close() when the agent session ends to disconnect all MCP server sessions and release resources (subprocess file descriptors, HTTP connections):

await registry.close()

MCP server configuration

MCP servers are configured via the axio-tui settings UI or programmatically:

stdio server (spawns a subprocess):

{
  "servers": [
    {
      "name": "filesystem",
      "command": ["npx", "-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
    },
    {
      "name": "github",
      "command": ["npx", "-y", "@modelcontextprotocol/server-github"],
      "env": {"GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_..."}
    }
  ]
}

HTTP server (connects to a running MCP HTTP endpoint):

{
  "servers": [
    {
      "name": "remote",
      "url": "https://my-mcp-server.example.com/mcp",
      "headers": {"Authorization": "Bearer my-token"},
      "timeout": 60.0
    }
  ]
}

Plugin registration

[project.entry-points."axio.tools.settings"]
mcp = "axio_tools_mcp.plugin:MCPPlugin"

Part of the axio ecosystem

axio · axio-tools-local · axio-tools-docker · axio-tui

License

MIT

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