MCP Server

@sathishj21

Basic information

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

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.

Comments

More Developer Tools MCP servers

LocalCan

Gives AI agents public URLs (tunnels) for localhost, live HTTP traffic inspection, snapshot publishing, and access control. Part of LocalCan, the ngrok alternative for Mac, Windows and Linux. Free plan.

Meticulous

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

DrUrls

DrUrls audits websites for SEO, and its MCP server lets Claude, ChatGPT, Claude Code, Cursor or VS Code work with those audits directly: list your sites with their latest score and grade, read each issue across SEO, perf

Cronwatch

cronwatchdev

CronWatch records every run of your scheduled jobs in your own database, and speaks up when one is missed, fails, gets stuck, runs slow or costs too much. CronWatch is free and open-source.