filesystem-mcp
llms.txt7 starsChanged 3 months agoMITView on GitHub
FastMCP 3.4+ server for file system operations, directory management, content search, and code intelligence (todos, symbols, project analysis, ruff lint, config validation) — with per-path concurrency-safe atomic writes. System monitoring and host context included. Docker tools are present but deprecated (docker-mcp owns that surface); git lives in git-github-mcp. Full documentation: llms-full.txt — complete tool catalog, response contracts, configuration, architecture, and troubleshooting. - 24 MCP tools, portmanteau grouped (file_ops, dir_ops, search_ops, container_ops, infra_ops, host_ops + compose, monitoring, agentic workflow, shutdown) -…
- Reads credentials
In this repository7 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/architect.mdcCursor rule
- llms-full.txtllms.txt
- full-stack-developerSkill
- mcp-server-architectSkill
The file
Files
# filesystem-mcp FastMCP 3.4+ server for file system operations, directory management, content search, and code intelligence (todos, symbols, project analysis, ruff lint, config validation) — with per-path concurrency-safe atomic writes. System monitoring and host context included. Docker tools are present but deprecated (docker-mcp owns that surface); git lives in git-github-mcp. > **Full documentation**: [llms-full.txt](llms-full.txt) — complete tool catalog, > response contracts, configuration, architecture, and troubleshooting. ## Key Facts - 24 MCP tools, portmanteau grouped (file_ops, dir_ops, search_ops, container_ops, infra_ops, host_ops + compose, monitoring, agentic workflow, shutdown) - file_ops: + get_file_hash, append_file, touch_file, compress, decompress - dir_ops: + copy_tree (shutil default, robocopy opt-in on Windows), move_directory - search_ops: + find_todos, find_symbols, validate_json, analyze_project, run_linter (ruff-only), validate_config - Dual transport: stdio (IDE clients) + HTTP streamable (webapp, LAN, Tailscale) - Atomic writes with per-path asyncio locks and automatic `.backup` files - Ports: backend 10742, webapp frontend 10743 (dev) - REST: /api/health, /api/status, /api/capabilities, /api/skills, /api/llm/discover, /api/llm/chat, /api/v1/diagnostics ## Docs - [Readme](README.md): Overview, quick start, Claude Desktop setup - [Install Guide](INSTALL.md): Installation and prerequisites - [Tools List](FILESYSTEM_MCP_TOOLS_LIST.md): Full tool catalog - [Technical Architecture](docs/TECHNICAL_ARCHITECTURE.md): Design and transport - [Troubleshooting](docs/TROUBLESHOOTING_FASTMCP_2.12.md): Known issues and fixes - [Changelog](CHANGELOG.md): Version history ## Configuration - [Pyproject](pyproject.toml): Python project configuration and dependencies - [Package](webapp/package.json): Node.js project configuration and dependencies - [Cargo](Cargo.toml): Rust (Tauri native wrapper) dependencies - [Environment Template](.env.example): Copy to `.env` and customize
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

