doc(readme): add OMOP MCP to community servers list

[JaerongA]

Description

Adding the OMOP MCP server to the third-party servers list in README.md. This server enables mapping clinical terminology to OMOP (Observational Medical Outcomes Partnership) concepts using MCP framework.

Server Details

• Server: N/A (adding third-party server listing, not modifying existing server)
• Changes to: README.md third-party servers section

Motivation and Context

OMOP MCP fills a critical gap in healthcare informatics by providing AI-powered mapping between clinical terminology and standardized OMOP concepts. This enables:

• Healthcare data standardization and interoperability
• Enabling LLMs to work with medical vocabularies (SNOMED, LOINC, RxNorm, etc.)

The server is actively maintained and provides production-ready functionality for the healthcare AI community.

How Has This Been Tested?

The OMOP MCP server itself has been tested with:

• Claude Desktop with successful clinical terminology mapping
• MCP protocol compliance verification
• Multiple clinical vocabularies
• Various OMOP table/field combinations

This PR only adds a listing to README.md and doesn't modify any server code.

Breaking Changes

None - this is only a documentation update adding a third-party server listing.

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation update

Checklist

• I have read the MCP Protocol Documentation
• My changes follows MCP security best practices
• I have updated the server's README accordingly
• I have tested this with an LLM client
• My code follows the repository's style guidelines
• New and existing tests pass locally
• I have added appropriate error handling
• I have documented all environment variables and configuration options

Additional context

This MCP server bridges the gap between AI assistants and healthcare data standards, enabling more reliable and efficient clinical data standardization.

Repository: https://github.com/OHNLP/omop_mcp