What operations does the server support?
It supports six tools: `list_directory`, `read_file`, `save_file`, `append_file`, `delete_this_file`, and `edit_file` (which offers line-based pattern matching and dry-run previews).
@asirulnik
基本情報
概要はまだありません
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp_server_filesystem_01": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Lists files and directories in the project directory
Reads the contents of a file
Creates or overwrites files atomically
Adds content to existing files
Removes files from the filesystem
Makes selective edits using pattern matching
MCP File System Server is a Model Context Protocol server that enables AI assistants (via Claude Desktop, VSCode/Cline extension, or other MCP-compatible systems) to perform file system operations—read, write, edit, delete—within a specified project directory. It is built for developers who want to collaborate with AI on local codebases through natural-language prompts.
Install the server by cloning the repository and running pip install -e . inside its directory. Then launch it with python -m src.main --project-dir /path/to/project, optionally setting --log-level and --log-file. Add the server’s configuration to your MCP client’s settings (e.g., Claude Desktop’s claude_desktop_config.json or Cline’s cline_mcp_settings.json) and restart the client.
list_directory: list files and directories in the project directoryread_file: read the contents of a filesave_file: atomically create or overwrite files with contentappend_file: append content to an existing filedelete_this_file: permanently delete a file from the filesystemedit_file: make selective edits using pattern matching with diff previewIt supports six tools: `list_directory`, `read_file`, `save_file`, `append_file`, `delete_this_file`, and `edit_file` (which offers line-based pattern matching and dry-run previews).
Python 3 (with a virtual environment recommended) and the dependencies installed via `pip install -e .`. The server uses FastMCP and can be run on Windows, macOS, or Linux.
Standard human-readable logs go to the console. Optionally, structured JSON logs can be written to a file specified with `--log-file`. Log level is configurable (DEBUG, INFO, WARNING, ERROR, CRITICAL).
All file paths are normalized and validated to stay within the project directory; path traversal attacks are blocked. Files are written atomically to prevent data corruption, and the `--project-dir` argument is required.
The server communicates via MCP’s standard transport (stdin/stdout) used by Claude Desktop and Cline. No external API endpoints or authentication are mentioned—access is governed by the MCP client’s auto-approval settings.
Go server implementing Model Context Protocol (MCP) for filesystem operations.

AI tools (Claude, ChatGPT, Gemini, Grok, etc.) generate HTML constantly, from reports to landing pages to prototypes, but there's no easy way to share it or know if anyone looked. HTMLvault turns any HTML into a clean, t
The SSE version of the MCP service is modified from the Filesystem MCP server
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