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* [ ] Gather ICD-10 data
* [x] Obtain dataset from CMS/CDC or Kaggle
* [ ] Download CSV of ICD-10-CM codes (\~70k entries)
* [ ] Load data into application or database
* [ ] Build search/lookup functionality
* [ ] Implement keyword filter for description matching
* [ ] Generate embeddings for each ICD description (offline)
* [ ] Build vector index (FAISS, Annoy, or numpy)
* [ ] Embed user query and perform nearest-neighbor search
* [ ] Combine code and description lookup into MCP API
* [ ] Accept input as code (lookup definition) or description (search codes)
* [ ] Return list of candidate codes with descriptions
* [ ] Integrate LLM for refinement (optional)
* [ ] Use GPT-4 or Claude to select best code from top-N results
* [ ] Prompt LLM to generate short rationale for selected code
* [ ] Cache LLM prompts and responses to conserve tokens
* [ ] Build MCP server (Gradio App)
* [ ] Create Gradio UI with text input and output area
* [ ] Implement backend logic to expose API endpoint or STDIO interface per MCP standards
* [ ] Tag Space with “mcp-server-track” and configure /api route
* [ ] Test connectivity with MCP client (e.g., Cursor IDE or Claude Desktop)
* [ ] Test with realistic inputs
* [ ] Simple case: “Type 1 diabetes mellitus” → expect E10.9
* [ ] Complex case: “Acute MI involving LAD” → expect I21.02 or related code
* [ ] Edge case: Typos or layman terms (e.g., “heart attack”) → verify semantic search or add spell-check
* [ ] Compare tool output to expected codes (use ChatGPT or reference lists)
* [ ] Optimize and cache
* [ ] Precompute embeddings for entire code database
* [ ] Cache embeddings of frequent queries
* [ ] Cache LLM explanations in memory or simple key-value store
* [ ] Choose deployment hardware (GPU-backed if running local embedding model; CPU if precomputed)
* [ ] Polish documentation & demo
* [ ] Write README.md with tool description, architecture outline, research citations, and sponsor acknowledgments
* [ ] Prepare 2–3 minute demo video showing Gradio UI and AI agent calling the MCP server
* [ ] Share project on community channels (Discord, YouTube) for feedback and visibility
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