filesystem-mcp
Enables AI agents to perform direct file operations within controlled local environments, bridging the gap between high-level reasoning and practical codebas…
Filesystem MCP server for AI assistants. Search, read, edit, and manage local files in directories you choose.
- Ask Claude to read and analyze local source code files
- Generate code updates and save them directly to your local files
- Find specific strings or patterns across multiple files in a directory
Enables AI agents to perform direct file operations within controlled local environments, bridging the gap between high-level reasoning and practical codebase manipulation. This reduces manual context switching and accelerates automated refactoring tasks.
Software engineers and DevOps teams requiring automated file manipulation and codebase analysis via AI-driven workflows.
https://github.com/j0hanz/filesystem-mcp
By j0hanz
How to Get It
claude mcp add filesystem-mcp -- npx -y filesystem-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Read and analyze local source code files
Trust Signals Auto-scanned
Data & Access
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 26 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 26 GitHub stars; contributors unknown; last commit 0d ago; license MIT.