MCP Server

@sathishj21

代码仓库

基本信息

分类

开发工具

传输方式

stdio

作者

sathishj21

关于 MCP Server

A modular FastAPI-based MCP (Model Context Protocol) server that supports reading local JSON and Excel files via HTTP API. Easily extensible for agents and automation tools like Flowsie AI or n8n. Includes Docker support and clean production-ready structure.

#mcp-server #fastapi #http-api

MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-sathishj21": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-server",
        "."
      ]
    }
  }
}

MCP Server 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🧠 Model Context Protocol (MCP) Server?

It is a modular FastAPI‑based MCP server designed for use in agent‑based systems and orchestration tools like Flowsie AI and n8n. It currently supports reading local JSON and Excel files and returns the data in JSON format.

How to use 🧠 Model Context Protocol (MCP) Server?

Install dependencies with pip install -r requirements.txt (requires Python 3.10+), then run locally with uvicorn app.main:app --reload --port 8000. Use the endpoint GET /local/read with a query parameter filename pointing to a file inside app/local_data/. A Docker image can be built with docker build -t mcp-server . and run with docker run -p 8000:8000 mcp-server.

Key features of 🧠 Model Context Protocol (MCP) Server

Reads local JSON and Excel files and returns JSON
Exposes a single REST endpoint: GET /local/read
Supports .json, .xlsx, and .xls file formats
Configurable via the app/configs/ directory
Can be run locally or inside a Docker container
Built with FastAPI and includes auto‑generated Swagger docs at /docs

Use cases of 🧠 Model Context Protocol (MCP) Server

Providing structured data from local files to AI agents or workflows
Integrating with orchestration tools like Flowsie AI and n8n
Serving as a lightweight file‑to‑JSON bridge for agent‑based systems
Testing MCP server functionality before adding additional connectors

常见问题

What file formats are supported?

The server supports `.json` files and Excel files (`.xlsx` / `.xls`). All data is returned as JSON (list or dict).

How do I specify which file to read?

Use the `GET /local/read` endpoint with a query parameter `filename`. The file must be placed inside the `app/local_data/` folder.

What are the runtime requirements?

Python 3.10 or higher is required. Dependencies are listed in `requirements.txt`.

Is there a Docker image available?

Yes. Build the image with `docker build -t mcp-server .` and run it with `docker run -p 8000:8000 mcp-server`. The server is then accessible at `http://localhost:8000/docs`.

What is the license?

The server is released under the MIT License, allowing free use and modification.

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