Cortellis MCP Server

Cortellis MCP Server

By uh-joan GitHub

An MCP server enabling AI assistants to search and analyze pharmaceutical data through Cortellis. Features comprehensive drug search and ontology exploration.

life-sciences competitive-intelligence
Overview

What is Cortellis MCP Server?

Cortellis MCP Server is a production-ready server that enables AI assistants to search and analyze pharmaceutical data through Cortellis, providing comprehensive drug search, ontology exploration, and real-time clinical trial data access.

How to use Cortellis MCP Server?

To use the Cortellis MCP Server, clone the repository from GitHub, install the necessary packages, set up your environment variables with your Cortellis API credentials, and then interact with the server using natural language prompts or API calls.

Key features of Cortellis MCP Server?

  • 🔍 Comprehensive Drug Search: Search by indication, phase, company, and access real-time drug development statuses.
  • 🧬 Ontology Exploration: Explore standardized medical terminology and navigate drug classifications.
  • 🔐 Secure Authentication: Environment-based credential management and secure API communication.
  • 🛠 Developer-Friendly: Clear API documentation and easy integration with AI assistants.

Use cases of Cortellis MCP Server?

  1. Drug discovery and development analysis.
  2. Clinical trial data retrieval and analysis.
  3. Pharmaceutical market research and competitive intelligence.

FAQ from Cortellis MCP Server?

  • Can I use Cortellis MCP Server for all pharmaceutical queries?

Yes! It supports a wide range of queries related to drug development and clinical trials.

  • Is there a cost associated with using Cortellis MCP Server?

The server is open-source and free to use, but you will need valid Cortellis API credentials.

  • How secure is the data handled by Cortellis MCP Server?

The server employs secure authentication, HTTPS encryption, and regular security audits to ensure data safety.

Content

Cortellis MCP Server

License: MIT PyPI version Python: 3.10+ PRs: Welcome

An MCP server enabling AI assistants to search and analyze pharmaceutical data through Cortellis. Perfect for competitive intelligence and pharmaceutical market research.

Features

  • 🔍 Drug Search: Search by indication, phase, company, and development status
  • 🧬 Ontology Exploration: Navigate standardized medical terminology and drug classifications
  • 🛠 Developer-Friendly: Clear documentation and easy integration with AI assistants
  • 🔐 Secure Authentication: Base64 token-based authentication for API access

Quick Start

Installation

# Using pip
pip install cortellis-mcp

# Or for development
git clone https://github.com/uh-joan/mcp-cortellis.git
cd mcp-cortellis
python -m venv venv
source venv/bin/activate  # On Unix/macOS
pip install -e .

Authentication Setup

The server uses a base64-encoded authentication token that combines your Cortellis username and password in the format username:password. This token must be provided in the CORTELLIS_AUTH environment variable.

To generate your token:

# On Unix/macOS
echo -n "your_username:your_password" | base64

# On Windows PowerShell
[Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes("your_username:your_password"))

Set up your environment:

  1. Copy .env.example to .env
  2. Replace your_base64_token with your generated token:
# In .env file
CORTELLIS_AUTH=your_base64_token  # e.g., dXNlcm5hbWU6cGFzc3dvcmQ=
MCP_WEBSOCKET=true
MCP_PORT=8765

IDE Integration

{
  "mcps": {
    "cortellis": {
      "command": ["python"],
      "args": ["-m", "cortellis_mcp"],
      "env": {
        "CORTELLIS_AUTH": "your_base64_token",
        "MCP_WEBSOCKET": "true",
        "MCP_PORT": "8765"
      }
    }
  }
}

Usage

Development Status Codes

  • DR: Discovery/Preclinical
  • C1: Phase 1 Clinical
  • C2: Phase 2 Clinical
  • C3: Phase 3 Clinical
  • PR: Pre-registration
  • R: Registered
  • L: Launched
  • DX: Discontinued
  • W: Withdrawn

Example Queries

  • "Search for drugs targeting obesity in phase 3"
  • "Find all launched drugs by Novo Nordisk"
  • "Explore ontology terms related to glucagon"

Python API

from cortellis_mcp import search_drugs, explore_ontology

# Search for Phase 3 obesity drugs
results = search_drugs(
    indication="obesity",
    phase="C3"
)

# Explore ontology terms
terms = explore_ontology(
    category="indication",
    term="diabetes"
)

Documentation

Security

  • Token-based authentication using base64 encoded credentials
  • HTTPS encryption for API communications
  • Request validation and rate limiting
  • Regular security audits
  • Secure environment variable handling

Support

For issues and feature requests, please use the GitHub issue tracker.

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