How does FastMCP handle tool documentation for Claude?

FastMCP automatically converts Python docstrings and type hints into the structured schemas that Claude uses to understand how and when to call specific tools.

What is FastMCP used for?

FastMCP is a Python framework used to build servers that follow the Model Context Protocol (MCP), enabling Claude and other LLMs to safely interact with local tools, data files, and external APIs.

Can I use FastMCP with Redis or databases?

Absolutely. FastMCP supports a wide variety of storage backends including Redis, Disk, DynamoDB, and MongoDB for state management and OAuth token persistence.

Does FastMCP support background tasks?

Yes, starting from version 2.14.0, FastMCP supports protocol-native background tasks that allow for long-running operations exceeding standard timeout limits with built-in progress tracking.

Is FastMCP compatible with the latest MCP specification?

Yes, FastMCP is updated regularly to support the latest MCP specifications, including features like sampling, elicitation, and the 2025-11-25 protocol standards.

FastMCP Python Server Framework

Name: FastMCP Python Server Framework
Author: evolv3ai

byevolv3ai

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API Development

Builds and deploys robust Model Context Protocol (MCP) servers in Python to expose tools, resources, and prompts to LLMs.

FastMCP is a high-level Python framework designed to streamline the development of Model Context Protocol (MCP) servers, allowing developers to easily connect their local tools, data, and logic to Claude. It provides production-ready features such as persistent storage backends (Redis, Disk, S3), background task management for long-running operations, and context-aware sampling for agentic workflows. By providing a structured, decorator-based API and proactive error prevention, FastMCP enables developers to build scalable, secure integrations that extend the capabilities of AI models with minimal boilerplate.

Key Features

01Protocol-native background tasks for non-blocking long-running operations

02Advanced context features for user elicitation and recursive LLM sampling

030 GitHub stars

04Decorator-based API for defining tools, resources, and prompts with ease

05Multiple storage backends including Redis, Disk, and encrypted Fernet options

06Provider-based architecture for hot-reloading and OpenAPI integration

Use Cases

01Developing agentic workflows where Claude can perform complex multi-step research

02Building data processing utilities that require real-time progress tracking

03Creating custom MCP servers to give Claude access to private APIs or databases

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add evolv3ai/claude-skills-archive fastmcp

For use in Claude.ai and ChatGPT

Download Skill