A research system comparing Retrieval-Augmented Generation (RAG) with Model Context Protocol (MCP) servers for obstetric medical knowledge retrieval and question answering. Implements parallel execution of RAG and MCP branches using LangGraph.
This is a client application, not an MCP server. It consumes MCP tools (tavily-search, search) from external servers but does not define or register its own tools. The two tools listed are proxied from Tavily and DuckDuckGo MCP servers; their definitions originate elsewhere. Tool definitions are inferred from usage in mcp_client.py, not explicitly registered in this codebase. Descriptions are generic ('Search tool from Tavily MCP server...'), under 20 chars of actionable detail. Input schemas show only a 'query' string with minimal description. No output schema documented. No error handling guidance, no parameter constraints, no idempotency hints.
Search tool from DuckDuckGo MCP server for web search functionality
Search tool from Tavily MCP server for web search functionality
This is a client application, not an MCP server. It does not define tools; it consumes them from external MCP servers. Tool definitions are inferred from usage, not explicitly registered.
Tool descriptions are generic and under 20 characters of meaningful content. 'Search tool from Tavily MCP server for web search functionality' does not explain when to use this vs. the DuckDuckGo search tool, what the output contains, or any prerequisites.
Input schema for both tools shows only 'query' parameter with minimal description. No constraints (length, format, examples), no guidance on query structure, no error cases documented.
No output schema documented. LLMs cannot plan downstream operations or extract structured data from search results. Responses are converted to strings (str(result)) in code, losing structure.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 28 | 2026-07-28+ | v2 |
No error handling guidance. Code catches exceptions and returns 'Error executing search: {str(e)}', raw error messages do not guide the LLM on recovery steps or retry logic.