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@medikode/mcp-server

v1.2.8

Published

Model Context Protocol (MCP) server for Medikode healthcare SaaS platform

Readme

@medikode/mcp-server

npm version License: ISC GitHub stars GitHub issues

Model Context Protocol (MCP) server for Medikode's AI-driven medical coding platform. This package enables AI assistants like Claude Desktop, Cursor, and ChatGPT to access Medikode's medical coding tools directly.

Medikode Dashboard - API Usage Trends

Medikode's AI-driven medical coding platform dashboard showing API usage trends and analytics

🌟 Features

  • 5 Powerful MCP Tools: Validate codes, QA charts, parse EOBs, calculate RAF scores, and more
  • AI Assistant Integration: Works with Claude Desktop, Cursor, ChatGPT, and other MCP-compatible clients
  • Secure: Uses your existing Medikode API keys with the same security and access controls
  • Fast: Direct API access with caching for optimal performance
  • Easy Setup: Simple configuration with npx - no local installation required

🚀 Quick Start

Installation

npm install -g @medikode/mcp-server

Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "medikode": {
      "command": "npx",
      "args": ["-y", "@medikode/mcp-server"],
      "env": {
        "MEDIKODE_API_KEY": "your_api_key_here"
      }
    }
  }
}

Cursor IDE

Add to your cursor_settings.json:

{
  "mcp": {
    "servers": {
      "medikode": {
        "command": "npx",
        "args": ["-y", "@medikode/mcp-server"],
        "env": {
          "MEDIKODE_API_KEY": "your_api_key_here"
        }
      }
    }
  }
}

🛠 Available Tools

1. validate_codes

Validates CPT/ICD-10 codes against clinical documentation.

Inputs:

  • chart_text (string, required): Provider note or chart excerpt
  • codes (array[string], required): CPT/ICD-10 codes to validate

Outputs:

  • valid (boolean): Whether codes are valid for the chart
  • recommendations (array[string]): Missing or conflicting codes

2. qa_chart

Performs a coding quality assurance check.

Inputs:

  • chart_text (string, required): Clinical documentation to review

Outputs:

  • issues_found (array[string]): Documentation or coding gaps
  • suggested_codes (array[string]): Recommended additional codes

3. parse_eob

Extracts structured data from Explanation of Benefits (EOB) documents.

Inputs:

  • eob_content (string, required): Raw EOB text (or PDF extracted text)

Outputs:

  • payer (string): Insurance payer name
  • claim_number (string): Claim reference number
  • total_billed (number): Total amount billed
  • total_allowed (number): Total amount allowed by payer
  • insurance_paid (number): Amount paid by insurance
  • patient_responsibility (number): Patient out-of-pocket amount

4. score_raf

Calculates RAF score and HCC capture from encounter documentation.

Inputs:

  • chart_text (string, required): Clinical encounter documentation

Outputs:

  • raf_score (float): Risk Adjustment Factor score
  • hcc_codes (array[string]): Hierarchical Condition Category codes

5. multi_validate

Composite workflow that validates chart coding and calculates RAF in one step.

Inputs:

  • chart_text (string, required): Clinical documentation
  • codes (array[string], optional): Optional codes to validate

Outputs:

  • validation_results (object): Results from validate_codes
  • raf_results (object): Results from score_raf

💡 Example Usage

Once configured, you can use the tools in your AI assistant:

User: "Validate these codes for this chart: 99213, I10, E11.9"

AI: I'll help you validate those codes using the validate_codes tool...
[Tool call to validate_codes]

Based on the validation results:
- Code 99213: Valid for established patient office visit
- Code I10: Valid for essential hypertension
- Code E11.9: Valid for type 2 diabetes without complications

🔑 Authentication

All tools require a valid Medikode API key. You can obtain one by:

  1. Signing up at medikode.ai
  2. Generating an API key in your account settings
  3. Setting the MEDIKODE_API_KEY environment variable

📊 Usage Tracking

All MCP tool usage is tracked and appears in your Medikode dashboard alongside regular API calls. This includes:

  • Number of API calls made
  • Charts processed
  • EOBs parsed
  • RAF scores calculated

🔧 Troubleshooting

Common Issues

MCP Server Not Found

  • Ensure Node.js and npm are installed
  • Verify the package is available via npx: npx @medikode/mcp-server --help

Authentication Errors

  • Check that your API key is correct and active
  • Verify the MEDIKODE_API_KEY environment variable is set
  • Ensure your API key has the required permissions

Tool Not Available

  • Restart your AI client after configuration changes
  • Verify the MCP server configuration is correct
  • Ensure your AI client supports MCP

📚 Documentation

🛠 Development

Prerequisites

  • Node.js 18.0.0 or higher
  • npm or yarn
  • Medikode API key

Local Development

  1. Clone the repository:

    git clone https://github.com/medikode/mcp-server.git
    cd mcp-server
  2. Install dependencies:

    npm install
  3. Set up environment variables:

    cp env.example .env
    # Edit .env with your API key
  4. Run in development mode:

    npm run dev
  5. Test the MCP server:

    npm run test:routing

Building

npm run build

Testing

# Test WebSocket connection
node test-websocket.js

# Test ChatGPT integration
python test-chatgpt-integration.py

# Test environment routing
node test-environment-routing.js

🤝 Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

Development Workflow

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/amazing-feature
  3. Commit your changes: git commit -m 'Add amazing feature'
  4. Push to the branch: git push origin feature/amazing-feature
  5. Open a Pull Request

Code Style

  • Use ESLint for JavaScript linting
  • Follow the existing code style
  • Add tests for new features
  • Update documentation as needed

🐛 Bug Reports

Found a bug? Please open an issue with:

  • Clear description of the problem
  • Steps to reproduce
  • Expected vs actual behavior
  • Environment details (Node.js version, OS, etc.)

💡 Feature Requests

Have an idea for a new feature? We'd love to hear it! Please open an issue with:

  • Clear description of the feature
  • Use case and benefits
  • Any implementation ideas you have

📊 Changelog

See CHANGELOG.md for a list of changes and version history.

🤝 Support

📄 License

ISC License - see LICENSE file for details.

🔗 Links

🙏 Acknowledgments