Geolocation

MCP Server generated by mcp.ag2.ai

python

GitHub Stars

python

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "priyansh4320-ip-geolocation-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "A JSON string containing the configuration.",
        "SECURITY": "Environment variables for security parameters (e.g., API keys).",
        "CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

You run an MCP (Multi-Agent Conversation Protocol) server that exposes a geolocation API client interface to your agents. This server enables agents to communicate through a defined MCP channel, connect to the local or remote MCP endpoint, and start interactions against the OpenAPI-backed geolocation data flow.

How to use

Launch the MCP server to start handling agent conversations. You can run it in stdio mode for local development, or use other supported transports as needed. To connect a client, point it at the server transport you started and begin sending MCP interactions. Ensure your client is configured to attach to the same transport protocol so messages flow smoothly between agents and the server.

How to install

Prerequisites: Python 3.9 or newer, plus pip and uv.

Clone the project directory.
Install development dependencies.

pip install -e ".[dev]"

If you prefer to use uv for installation and execution, you can run the same editable install through uv as shown.


3. Run static checks and tests as needed (optional but recommended during development).

ruff check ruff format ./scripts/static-analysis.sh ./scripts/test.sh ./scripts/test-cov.sh pre-commit install

## Additional notes

You can start the MCP server in stdio mode with a direct Python command. This mode integrates with local development tools and allows you to interact with the server programmatically in tests or during manual experimentation.

## Available tools

### ruff

Lints and formats the codebase to ensure consistent style and syntax.

### mypy

Performs static type checking to catch type errors early.

### pytest

Runs unit tests to verify functionality and regression coverage.

### pre-commit

Runs a suite of hooks before commits to keep code quality high.

### hatch

Builds and publishes the MCP server package.

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