Directory Registration
Overview
This document outlines the strategy and implementation steps for registering BondMCP on major Model Context Protocol (MCP) directories. Being listed on these directories is crucial for discovery by AI developers and models looking to integrate with healthcare data.
Target MCP Directories
MCP Market (mcp.market)
Primary marketplace for MCP servers and capabilities
High visibility among AI developers and model providers
Supports healthcare category listings
mcp.so
Developer-focused directory with technical documentation
Supports capability discovery and testing
Popular among enterprise AI implementations
Anthropic MCP Directory
Official directory maintained by Anthropic
High visibility for Claude model users
Supports verified healthcare integrations
OpenAI Plugin Directory
Supports MCP-compatible listings
Reaches GPT model users
Healthcare category available
Registration Requirements
Common Requirements
Server base URL
Server name and description
Available capabilities and parameters
Authentication methods
Health check endpoint
OpenAPI schema (if available)
Contact information
MCP Market Specific
Logo (512x512px)
Category selection (Healthcare)
Pricing information
Terms of service URL
Privacy policy URL
mcp.so Specific
GitHub repository URL
Documentation URL
Example code snippets
Test credentials
Anthropic Directory Specific
Verification of healthcare credentials
Data handling documentation
Safety protocols
Sample prompts
OpenAI Directory Specific
Manifest file
Legal attestation
Data privacy documentation
Implementation Steps
1. Prepare Registration Assets
Create server logo and branding materials
Draft comprehensive server description highlighting healthcare focus
Document all available capabilities with detailed parameters
Prepare code examples for different programming languages
Create developer documentation
2. Set Up Required Endpoints
Implement MCP discovery endpoint (
/.well-known/mcp-configuration)Create health check endpoint
Implement OpenAPI schema endpoint
Set up authentication endpoints
3. MCP Market Registration
Create account on MCP Market
Complete organization profile
Submit server listing with all required information
Set up monitoring for approval status
4. mcp.so Registration
Create account on mcp.so
Link GitHub repository
Submit server information
Upload documentation and examples
5. Anthropic Directory Registration
Apply for healthcare provider verification
Submit server information
Provide safety documentation
Complete review process
6. OpenAI Directory Registration
Create plugin manifest
Submit for review
Complete legal attestation
Provide test credentials
Monitoring and Optimization
Set up monitoring for directory listing status
Track traffic from each directory
Collect user feedback on discovery experience
Optimize listings based on performance metrics
Implementation Code
MCP Configuration Endpoint
Create the well-known MCP configuration endpoint at /.well-known/mcp-configuration:
@app.route('/.well-known/mcp-configuration')
def mcp_configuration():
return jsonify({
"name": "BondMCP Healthcare MCP",
"description": "Healthcare data and analysis capabilities for AI models",
"contact_email": "[email protected]",
"version": "1.0.0",
"auth": {
"type": "api_key",
"location": "header",
"key": "X-API-Key"
},
"servers": [
{
"id": "lab-results",
"url": "https://api.bondmcp.com/mcp/servers/lab-results",
"description": "Laboratory results interpretation"
},
{
"id": "vitals",
"url": "https://api.bondmcp.com/mcp/servers/vitals",
"description": "Vital signs data and analysis"
}
],
"capabilities_url": "https://api.bondmcp.com/mcp/capabilities",
"documentation_url": "https://docs.bondmcp.com/mcp",
"health_check_url": "https://api.bondmcp.com/health",
"logo_url": "https://bondmcp.com/assets/mcp-logo.png",
"categories": ["healthcare", "medical", "lab-results", "vitals"]
})Health Check Endpoint
Implement a health check endpoint:
@app.route('/health')
def health_check():
# Check all MCP servers
servers_status = {}
for server_id in server_registry.list_servers():
try:
# Basic check that server is responsive
server = server_registry.get_server(server_id)
servers_status[server_id] = "healthy"
except Exception:
servers_status[server_id] = "unhealthy"
# Overall health is healthy only if all servers are healthy
overall_status = "healthy" if all(status == "healthy" for status in servers_status.values()) else "degraded"
return jsonify({
"status": overall_status,
"version": "1.0.0",
"timestamp": datetime.utcnow().isoformat(),
"servers": servers_status
})Directory Listing Content
MCP Market Listing
Title: BondMCP Healthcare MCP
Short Description: One Language for Your Body, Doctors, and AI - BondMCP provides secure, HIPAA-compliant healthcare data access and analysis for AI models.
Long Description:
BondMCP is a trusted healthcare AI protocol providing standardized access to medical data and analysis capabilities. Our MCP implementation allows AI models to securely access and interpret lab results, vital signs, and other health data while maintaining strict compliance with healthcare regulations.
Key Features:
- Lab results interpretation with medical-grade accuracy
- Vital signs analysis and tracking
- Wearable device data integration
- Medication and supplement recommendations
- HIPAA-compliant data handling
BondMCP uses a tri-vote ensemble of leading medical AI models (Claude3, GPT-4o, MedLM) to ensure reliable and accurate healthcare insights. All capabilities are exposed through standardized MCP interfaces for seamless integration with AI models and applications.
Our healthcare-specific MCP extensions (HMCP) provide specialized capabilities for clinical workflows, including FHIR resource mappings and medical terminology normalization across SNOMED, LOINC, and RxNorm.Categories: Healthcare, Medical Data, AI Integration, Clinical Decision Support
Tags: #healthcare #labresults #vitalsigns #medicalAI #HIPAA #FHIR
mcp.so Listing
Title: BondMCP - Healthcare MCP
Description:
BondMCP provides healthcare-specific MCP servers for AI models to access and analyze medical data. Our implementation follows MCP best practices while adding healthcare-specific extensions for clinical workflows.
## Available Servers
- **Lab Results Server**: Interpret laboratory test results with medical-grade accuracy
- **Vitals Server**: Access and analyze vital signs data
- **Wearables Server**: Integrate with fitness and health devices
- **Medication Server**: Access medication history and recommendations
## Integration
```python
import requests
# Discover BondMCP capabilities
response = requests.get("https://api.bondmcp.com/.well-known/mcp-configuration")
config = response.json()
# Get lab results interpretation
lab_data = {
"lab_results": {
"glucose": 120,
"cholesterol": 180
}
}
headers = {"X-API-Key": "YOUR_API_KEY"}
response = requests.post(
"https://api.bondmcp.com/mcp/servers/lab-results/request",
json={
"capability_id": "interpret-labs",
"parameters": lab_data
},
headers=headers
)
interpretation = response.json()
print(interpretation["result"]["interpretation"])See our documentation for more examples and integration guides.
## Next Steps After Registration
1. **Monitor Approval Status**: Check daily for approval status and respond promptly to any requests for additional information
2. **Announce Listings**: Update website and documentation with directory listing information
3. **Track Traffic**: Implement analytics to track traffic from each directory
4. **Gather Feedback**: Collect user feedback on discovery experience
5. **Optimize Listings**: Regularly update listings based on performance and user feedbackLast updated
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