Explorium API MCP Server

This MCP server is used to interact with the Explorium API.

Note: this is the README for developing the MCP server. For usage instructions, see the README-pypi.md.

Setup

Clone the repository:

git clone https://github.com/explorium-ai/mcp-explorium.git
cd mcp-explorium

Install uv and activate the virtual environment:

pip install uv
uv sync --group dev

Running Locally

When developing locally, use local_dev_server.py to expose the MCP server to local clients.

You can test it with the MCP Inspector:

mcp dev local_dev_server.py

Create an .env file in the root of the repository with an EXPLORIUM_API_KEY environment variable if it’s not already configured.

Usage with Claude Desktop

Follow the official guide to install Claude Desktop and set it up to use MCP servers:

https://modelcontextprotocol.io/quickstart/user

Then, add this entry to your claude_desktop_config.json file:

{
  "mcpServers": {
    "Explorium": {
      "command": "<UV_INSTALL_PATH>",
      "args": [
        "run",
        "--directory",
        "<REPOSITORY_PATH>",
        "mcp",
        "run",
        "local_dev_server.py"
      ],
      "env": {
        "EXPLORIUM_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Be sure to replace all the <PLACEHOLDERS> with the actual values.

Run which uv to get your uv install path.

Usage with Cursor

Cursor has built-in support for MCP servers.

To configure it to use the Explorium MCP server, go to Cursor > Settings > Cursor Settings > MCP and add an “Explorium” entry with this command:

uv run --directory repo_path mcp run local_dev_server.py

Make sure to replace repo_path with the actual path to the repository.

You may turn on “Yolo mode” in Cursor settings to use tools without confirming under Cursor > Settings > Cursor Settings > Features > Chat > Enable Yolo mode.

Note: local usage will not work if dev dependencies are not installed, or if the virtual environment is not activated.

Building and Deploying

To build the MCP server, bump the version in pyproject.toml, then run:

uv build

This will create a dist directory with the built package.

You may then deploy the package to PyPI using the following command:

twine upload dist/*