MCP Server

@otoTree

Basic information

About MCP Server

No overview available yet

MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-ototree": {
      "command": "uv",
      "args": [
        "init",
        "project",
        "-",
        "name"
      ]
    }
  }
}

MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP?

MCP (Model Context Protocol) is a client tool that exposes local MCP servers through Flask, enabling platforms like Coze, Dify, and FastGPT to interact with local resources via self-hosted intranet penetration.

How to use MCP?

Set up the environment with uv, create a project directory, activate a virtual environment, and install dependencies from pyproject.toml. Configure mcp_server.json with server definitions and set environment variables in a .env file. Run python server.py to start the Flask server. Use POST requests to endpoints like /list_tool, /call_tool, /list_server, /list_files, and GET requests to /get_download_link/<secret_key>/<filename>.

Key features of MCP

Exposes local MCP servers via HTTP API.
Supports multiple server definitions in a JSON config.
Provides endpoints to list tools, call tools, and list servers.
Includes file listing and download link generation.
Uses secret key authentication for API requests.
Works with self-signed certificates for local development.

Use cases of MCP

Integrate local MCP tools (e.g., weather, filesystem) with cloud AI platforms.
Allow Coze, Dify, or FastGPT to call local Python scripts via API.
Securely expose file management capabilities to external services.
Debug and test MCP server interactions with a simple REST interface.

Frequently asked questions

What is required to run MCP?

You need `uv` installed, a virtual environment, and dependencies from `pyproject.toml`. A `mcp_server.json` file defines the servers to expose, and a `.env` file holds sensitive keys.

How do I configure servers in MCP?

Edit `mcp_server.json` with entries containing `desc`, `command`, and `args`. Each entry represents an MCP server that will be exposed via the Flask API.

Is authentication supported?

Yes, all API endpoints require a `secret_key` in the request body (or URL path for downloads). The secret is defined in the `.env` file.

Can I use MCP in production?

The README recommends using formal SSL certificates from a trusted CA (e.g., Let’s Encrypt) for cloud deployment, as self-signed certificates may cause issues on platforms like Coze.

What transports does MCP support?

MCP uses HTTP POST and GET endpoints via a Flask server. The default transport is REST over HTTP/HTTPS. No other transports (like WebSocket) are mentioned.

Comments

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