MCP Servers

MCP Server

A FastAPI-based Model Context Protocol server that exposes herd data through a discoverable API, with local and containerized deployment options.

Category

README

MCP Proof of Concept

This repository contains a simple Model Context Protocol (MCP) server implemented with FastAPI. The goal is to expose herd data through a discoverable, versioned API that can be deployed to AWS Fargate.

Running locally

Install dependencies:

The database path can be configured via the DATABASE_PATH environment variable. If not set it defaults to mcp.db inside the working directory.
```
pip install -r requirements.txt
```
Seed the SQLite database:
```
python -m app.seed
```
Start the API server:
```
uvicorn app.main:app --reload
```
Authenticate with the token fake-super-secret-token when calling the API.

The MCP discovery file is available at model_context.yaml.

Using the agent

An agent package is provided to interact with the MCP server. After the server is running you can list the herd data like so:

python -m agent http://localhost:8000 --token fake-super-secret-token

The agent reads model_context.yaml to discover the API path and returns the JSON response from the server. For full YAML support install the optional PyYAML dependency; otherwise a limited built-in parser is used.

Running tests

pytest -q

Container

A Dockerfile is provided to run the server in a container. Build with:

docker build -t mcp .

Terraform

The terraform directory contains a minimal configuration showing how the container could be deployed to AWS (e.g. Fargate). It creates an ECR repository for the image.

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