* [ ] 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