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's AI-driven medical coding platform dashboard showing API usage trends and analytics
- 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
npm install -g @medikode/mcp-server
Add to your claude_desktop_config.json
:
{
"mcpServers": {
"medikode": {
"command": "npx",
"args": ["-y", "@medikode/mcp-server"],
"env": {
"MEDIKODE_API_KEY": "your_api_key_here"
}
}
}
}
Add to your cursor_settings.json
:
{
"mcp": {
"servers": {
"medikode": {
"command": "npx",
"args": ["-y", "@medikode/mcp-server"],
"env": {
"MEDIKODE_API_KEY": "your_api_key_here"
}
}
}
}
}
Validates CPT/ICD-10 codes against clinical documentation.
Inputs:
chart_text
(string, required): Provider note or chart excerptcodes
(array[string], required): CPT/ICD-10 codes to validate
Outputs:
valid
(boolean): Whether codes are valid for the chartrecommendations
(array[string]): Missing or conflicting codes
Performs a coding quality assurance check.
Inputs:
chart_text
(string, required): Clinical documentation to review
Outputs:
issues_found
(array[string]): Documentation or coding gapssuggested_codes
(array[string]): Recommended additional codes
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 nameclaim_number
(string): Claim reference numbertotal_billed
(number): Total amount billedtotal_allowed
(number): Total amount allowed by payerinsurance_paid
(number): Amount paid by insurancepatient_responsibility
(number): Patient out-of-pocket amount
Calculates RAF score and HCC capture from encounter documentation.
Inputs:
chart_text
(string, required): Clinical encounter documentation
Outputs:
raf_score
(float): Risk Adjustment Factor scorehcc_codes
(array[string]): Hierarchical Condition Category codes
Composite workflow that validates chart coding and calculates RAF in one step.
Inputs:
chart_text
(string, required): Clinical documentationcodes
(array[string], optional): Optional codes to validate
Outputs:
validation_results
(object): Results from validate_codesraf_results
(object): Results from score_raf
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
All tools require a valid Medikode API key. You can obtain one by:
- Signing up at medikode.ai
- Generating an API key in your account settings
- Setting the
MEDIKODE_API_KEY
environment variable
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
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
- Node.js 18.0.0 or higher
- npm or yarn
- Medikode API key
-
Clone the repository:
git clone https://github.com/medikode/mcp-server.git cd mcp-server
-
Install dependencies:
npm install
-
Set up environment variables:
cp env.example .env # Edit .env with your API key
-
Run in development mode:
npm run dev
-
Test the MCP server:
npm run test:routing
npm run build
# Test WebSocket connection
node test-websocket.js
# Test ChatGPT integration
python test-chatgpt-integration.py
# Test environment routing
node test-environment-routing.js
We welcome contributions! Please see our Contributing Guidelines for details.
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature
- Commit your changes:
git commit -m 'Add amazing feature'
- Push to the branch:
git push origin feature/amazing-feature
- Open a Pull Request
- Use ESLint for JavaScript linting
- Follow the existing code style
- Add tests for new features
- Update documentation as needed
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.)
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
See CHANGELOG.md for a list of changes and version history.
- Issues: GitHub Issues
- Documentation: docs.medikode.ai
- Email: [email protected]
- Discord: Join our community
ISC License - see LICENSE file for details.
- Built with Model Context Protocol
- Powered by Medikode medical coding platform
- Thanks to all our contributors and users!