🧠 Model Context Protocol (MCP) Server

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

FAQ from 🧠 Model Context Protocol (MCP) Server

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.