Enables semantic search over local markdown specs, RFCs, and docs using Ollama and LanceDB, allowing AI agents to find relevant information by meaning rather than exact keywords.
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process.env. You'll be asked to provide them before it can run.CLAUDE_PROJECT_DIRDB_PATH— project>/.mcp-search Where LanceDB index is storedEMBEDDING_BACKEND— ollama Vector provider: ollama or geminiGEMINI_API_KEY— _(Required)_ Required when EMBEDDING_BACKEND=geminiGEMINI_BASE_URLGEMINI_EMBEDDING_DIMENSIONS— 768 Vector width (128–3072)GEMINI_EMBEDDING_MODEL— gemini-embedding-001 Embedding model to useMIN_SCORE— 0.44 Default similarity thresholdOLLAMA_BASE_URLOLLAMA_EMBEDDING_MODEL— qwen3-embedding:0.6b Embedding model to useSPECS_DIR— project>/specs Absolute path to markdown specs[](https://m8ven.ai/mcp/lemuelflores-spec-search-mcp-08kmsk)