easymcp

MCP.Pizza Chef: promptmesh

EasyMCP is a high-performance Python SDK that provides a complete rewrite of the Model Context Protocol (MCP) client. It offers a high-level API through the ClientManager class to manage multiple MCP servers concurrently, enabling seamless initialization, addition, removal, and listing of MCP servers and tools. EasyMCP simplifies integration with MCP servers using Python, supporting asynchronous operations and flexible server management for developers building AI-enhanced workflows and agents.

Use This MCP client To

Manage multiple MCP servers from a single Python client Initialize and configure MCP servers asynchronously Add or remove MCP servers dynamically during runtime List available MCP servers and their tools programmatically Integrate MCP client functionality into Python-based AI workflows Coordinate multi-server MCP environments for complex agent orchestration

README

EasyMCP

EasyMCP is a complete rewrite of the model context protocol (MCP) in Python.

Installation

uv add easymcp

Usage

The high level API exposes a ClientManager class that can be used to manage multiple MCP servers.

import asyncio
from easymcp.client.ClientManager import ClientManager
from easymcp.client.transports.stdio import StdioServerParameters

mgr = ClientManager()

searxng = StdioServerParameters(
    command="uvx",
    args=["mcp-searxng"],
)

timeserver = StdioServerParameters(
    command="uvx",
    args=["mcp-timeserver"],
)

servers = {
    "searxng": searxng,
    "timeserver": timeserver,
}

async def main():
    # initialize the client manager
    await mgr.init(servers=servers)

    # list servers
    print(mgr.list_servers())

    # remove a server
    await mgr.remove_server("searxng")

    # add a server
    await mgr.add_server("searxng", searxng)

    # list tools - these are namespaced by server name automatically
    # {server name}.{tool name}
    print(await mgr.list_tools())

    # call tool
    print(await mgr.call_tool("timeserver.get-current-time", {}))

    # list resources - these are namespaced by server name automatically
    # mcp-{server name}+{resource uri}
    print(await mgr.list_resources())

    # read resource
    print(await mgr.read_resource("mcp-timeserver+datetime://Africa/Algiers/now"))

    await asyncio.Future()

asyncio.run(main())

Core Features

  • list tools/resources/prompts caching out of the box
  • automatic cache invalidation on tool/resource/prompt change notifications
  • out of the box support for parallel requests to servers
  • full lifecycle management of servers
  • dynamic server addition/removal
  • namespaced tools/resources/prompts
  • lightweight asyncio native implementation

Why namespace tools?

Namespaced tools remove need to perform a lookup to find the correct tool. This means:

  • faster tool calls
  • tool calls can be routed across many MCP hosts at scale
  • mcp servers do not need globally unique tool names

Why namespace resources?

Resources are namespaced in a way that makes it easy to make a resource URI to a specific server. You can:

  • check if a URL needs to be resolved via mcp by checking if it starts with mcp
  • check what server to resolve the URI with
  • ingest resources into a search system like elastic search without having to store metadata about the server
  • completely eliminate the need to map URIs to servers via a database or lookup table

Comparison of classes to other MCP libraries

easyMCP modelcontextprotocol/python-sdk
ClientManager manages multiple MCP servers
ClientSession ClientSession manages a single MCP server
StdioTransport stdio_client raw subprocess transport

License

This project is licensed under the MIT License - see the LICENSE file for details.

easymcp FAQ

How do I install EasyMCP?
You can install EasyMCP using the command `uv add easymcp` in your terminal.
What programming language is EasyMCP built for?
EasyMCP is a Python SDK designed for managing MCP clients and servers.
Can EasyMCP manage multiple MCP servers simultaneously?
Yes, EasyMCP's ClientManager class allows you to manage multiple MCP servers concurrently.
Does EasyMCP support asynchronous operations?
Yes, EasyMCP supports asynchronous initialization and management of MCP servers using Python's asyncio.
How do I add or remove MCP servers using EasyMCP?
You can add or remove servers dynamically using the ClientManager's `add_server` and `remove_server` methods.
Is EasyMCP compatible with different MCP servers?
Yes, EasyMCP can manage any MCP server that follows the MCP protocol, making it flexible for various server implementations.
What are the main components of EasyMCP?
The main component is the ClientManager class, which handles server management and tool listing.
Can EasyMCP be used to build AI-enhanced workflows?
Yes, EasyMCP enables developers to integrate and orchestrate multiple MCP servers for complex AI workflows.