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MCP Server

@sathishj21

Repository

Basic information

Category

Developer Tools

Transports

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Author

sathishj21

About 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 config

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

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

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 🧠 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

Frequently asked questions

1

What file formats are supported?

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

2

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.

3

What are the runtime requirements?

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

4

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`.

5

What is the license?

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

Comments

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