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Chunk, embed, and index code for semantic context in AI coding assistants.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "code-context-mcp" yet — see the docs or source repo.
Build a semantic code index for this repository: chunk source files by file and function, generate embeddings, store them in ChromaDB, and return MCP service details for context retrieval.
Returns chunking and embedding results plus MCP context service details usable by an AI assistant.
For the issue 'user login failure,' retrieve the most relevant modules, functions, and call paths from the indexed codebase and prepare semantic context for an AI coding assistant.
Provides the most relevant code snippets, locations, and context summaries to support AI-assisted debugging and fixes.
I’m about to refactor the payment module. Extract code context related to payment flow, interface definitions, and error handling from the vector store, then rank it by importance.
Returns a ranked list of key code context needed for refactoring, helping AI understand dependencies and impact.
Read, search, and update codebase documentation context through MCP.
Embed your codebase for fast semantic search with Graph RAG.
Provides code context, memory, search, and AI tooling for developers.
Build semantic memory and structural code indexes for persistent AI project context.
Index local codebases for hybrid search and relevant context retrieval.
Search codebases semantically to find relevant snippets and implementation context fast.