Lifesciences

MCP Server generated by mcp.ag2.ai

python

0

GitHub Stars

python

Language

4 months ago

First Indexed

3 weeks 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": {
    "ag2-mcp-servers-cloud-life-sciences-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "JSON config string",
        "SECURITY": "Security parameters like API keys",
        "CONFIG_PATH": "Path to JSON config file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

You run an MCP (Model Context Protocol) Server to expose a specific API through a consistent, decoupled interface that clients can consume efficiently. This server lets you connect your MCP clients to the Lifesciences v2beta API, enabling standardized requests and responses while keeping implementation details on the server side.

How to use

Start the MCP server in stdio mode and connect your MCP client to it. The server is designed to be run locally and then consumed by your client through the MCP transport, enabling you to issue operations against the Lifesciences API as if you were calling it directly.

How to install

Prerequisites you need before installing and running the MCP server are Python 3.9 or newer and the package tools pip and uv.

# 1. Clone the service repository
# Replace <repository-url> with the actual repository URL
git clone <repository-url>
cd mcp_server

# 2. Install development dependencies
pip install -e ".[dev]"

# Alternative using uv
uv pip install --editable ".[dev]"

Run linting, static checks, and tests as needed to ensure code quality before starting the server.

# Linting
ruff check
ruff format

Start the MCP server in stdio mode once dependencies are installed.

python mcp_server/main.py stdio

Additional configuration and notes

Configuration can be provided in several ways. You can specify a JSON configuration file path via the CONFIG_PATH environment variable, supply a JSON string through CONFIG, or configure security parameters via SECURITY. The runtime reads these settings to determine how the MCP server should operate.

Environment variables you may use include:

CONFIG_PATH: Path to a JSON configuration file (for example, mcp_server/mcp_config.json).
CONFIG: A JSON string containing the configuration.
SECURITY: Security-related parameters such as API keys or tokens.

If you want to run tests or perform static analysis during development, you can use the project’s helper scripts for those tasks. Ensure you have the appropriate tooling installed as described in the install steps.

Available tools

MCP runtime

Runs an MCP server instance and serves a specified transport mode (stdio in this setup).