Filesys 📁

Created By
YothisisTroya year ago
This is a Filesystem MCP server that could allow an LLM to read and list files from a specified directory on your local machine.
Overview

What is Filesys?

Filesys is a Filesystem MCP server that enables an AI agent to read and list files from a specified directory on your local machine, facilitating seamless file management through the Model Context Protocol (MCP).

How to use Filesys?

To use Filesys, download the necessary files from the GitHub repository, launch the server, and start managing your files with the AI agent's assistance.

Key features of Filesys?

  • Allows AI agents to interact with the local filesystem.
  • Supports file reading and listing operations.
  • Built on the Model Context Protocol for efficient file management.

Use cases of Filesys?

  1. Enabling AI agents to access and manage local files.
  2. Streamlining file operations for developers using AI.
  3. Integrating file management capabilities into AI-driven applications.

FAQ from Filesys?

  • Can Filesys work with any local directory?

Yes! Filesys can read and list files from any specified directory on your local machine.

  • Is there any setup required before using Filesys?

Yes! You need to download and launch the server to start using it.

  • What programming language is Filesys built with?

Filesys is built using Python.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
YothisisTroy
Star
2
Language
Python
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago