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Practical MCP with FastMCP & LangChain

FastMCP ChatGPT GPT LangChain Python

Engineering the Agentic Experience

Practical MCP with FastMCP & LangChain
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FastMCP 3.0 Released: Community-Driven Enhancements Unveiled

FastMCP

FastMCP 3.0 is now generally available. It keeps the @mcp.tool() API but rebuilds the internals around components + providers + transforms, adds a CLI, and ships production features like component versioning, per-component auth + OAuth additions, OpenTelemetry tracing, background tasks, pagination, tool timeouts, and hot reload. The project moved from jlowin/fastmcp to PrefectHQ/fastmcp on GitHub, and upgrading is supported via dedicated guides for FastMCP 2 and MCP SDK users.

FastMCP 3.0 Released: Community-Driven Enhancements Unveiled
FastMCP is an open-source Python framework designed to simplify the development of Model Context Protocol servers. It allows developers to define MCP components such as tools, resources, and prompts using decorators, and to organize them through a modular architecture built around providers and transforms. Providers determine where components originate, including local code, directories, OpenAPI specifications, or remote MCP servers. Transforms modify components as they flow to clients, enabling namespacing, filtering, versioning, and visibility control.

The framework supports component versioning, per-component authorization, and middleware for cross-cutting concerns such as authentication and logging. It includes a built-in command-line interface for listing, calling, discovering, and installing MCP servers. FastMCP also supports session-scoped state, background task execution, OpenTelemetry tracing, pagination for large component sets, and transport options including stdio and HTTP-based protocols.

FastMCP is intended for developers building agent-compatible backends and structured tool interfaces for large language model systems that implement the Model Context Protocol.