by anthropic
Learn how to use Python to read a file and manipulate local files safely through the Filesystem API.
Provides secure filesystem operations for AI agents with batch processing to read, write, and search files while staying confined to your project directory.
Filesystem is an official MCP server published by anthropic that provides AI assistants with tools and capabilities via the Model Context Protocol. Learn how to use Python to read a file and manipulate local files safely through the Filesystem API. This server exposes 14 tools that AI clients can invoke during conversations and coding sessions.
You can install Filesystem in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
NOASSERTION
Filesystem is released under the NOASSERTION license.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Filesystem against two servers with overlapping tools; this profile had the clearer scope statement.
Filesystem is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Filesystem is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Filesystem reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired Filesystem into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: Filesystem surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Filesystem has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: Filesystem is the kind of server we cite when onboarding engineers to host + tool permissions.
Filesystem reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Filesystem is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources.
[!IMPORTANT] If you are looking for a list of MCP servers, you can browse published servers on the MCP Registry. The repository served by this README is dedicated to housing just the small number of reference servers maintained by the MCP steering group.
[!WARNING] The servers in this repository are intended as reference implementations to demonstrate MCP features and SDK usage. They are meant to serve as educational examples for developers building their own MCP servers, not as production-ready solutions. Developers should evaluate their own security requirements and implement appropriate safeguards based on their specific threat model and use case.
The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources. Typically, each MCP server is implemented with an MCP SDK:
These servers aim to demonstrate MCP features and the official SDKs.
The following reference servers are now archived and can be found at servers-archived.
[!NOTE] The server lists in this README are no longer maintained and will eventually be removed.
Official integrations are maintained by companies building production ready MCP servers for their platforms.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
