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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.
Turn any LLM into a codebase expert with search, mapping, and security insights.
Read, edit, and refactor code precisely with AST-based, token-efficient operations.
Read, search, and update codebase documentation context through MCP.
Gives AI coding agents a structural map of your repository fast.
Search codebases semantically with natural language and retrieve relevant context.
Provides code context, memory, search, and AI tooling for developers.