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FastMCP v2 MCP Server

@Sobroinc

基本信息

分类

云与基础设施

许可证

Apache-2.0 license

传输方式

stdio

作者

Sobroinc

关于 FastMCP v2 MCP Server

FastMCP server containerized for deployment in Google Kubernetes Engine alongside enhanced-mcp-agent

FastMCP v2 MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "fast-mcp": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "fastmcp"
      ]
    }
  }
}

FastMCP v2 MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is FastMCP v2 🚀?

FastMCP v2 is the standard Python framework for building and interacting with Model Context Protocol (MCP) servers and clients. It provides a high-level, Pythonic interface for exposing tools, resources, and prompts, and includes advanced features like client support, server composition, authentication, and automatic generation from OpenAPI specs.

How to use FastMCP v2 🚀?

Install with uv pip install fastmcp, then create a server instance with FastMCP("name") and decorate Python functions as tools, resources, or prompts. Run locally with fastmcp run server.py or mcp.run(). Use the Client class to connect to any MCP server programmatically via stdio, SSE, or in-memory transports.

Key features of FastMCP v2 🚀?

  • Build tools, resources, and prompts with minimal boilerplate
  • Client support for stdio, SSE, and in-memory transports
  • Server composition and proxy servers for remote MCP servers
  • Automatic generation of MCP servers from OpenAPI specs
  • Built-in in-memory testing via FastMCPTransport
  • Authentication and security features for production deployments

Use cases of FastMCP v2 🚀?

  • Expose custom Python functions as tools for LLMs
  • Serve static or dynamic data resources to AI applications
  • Build reusable prompt templates for AI assistants
  • Convert existing OpenAPI specifications into MCP servers
  • Test MCP server logic without network overhead using in-memory transport
  • Unify multiple MCP servers under a single client interface

常见问题

1

What is the Model Context Protocol (MCP)?

MCP is a standardized way for LLM applications to securely access data and functionality. It is described as "the USB-C port for AI" and lets servers expose resources, tools, and prompts.

2

How does FastMCP v2 differ from the official MCP Python SDK?

FastMCP 1.0 was incorporated into the official low-level Python SDK. FastMCP 2.0 is a complete toolkit that goes beyond the core protocol, adding client libraries, authentication, server composition, OpenAPI generation, testing tools, and production-ready infrastructure.

3

What transports does the FastMCP Client support?

The Client supports Stdio, SSE, and In-Memory transports. It often auto-detects the correct transport from the connection string and also supports connecting to multiple servers through a unified

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