Claude Context

Claude Context is Zilliz's open-source MCP server for semantic code search: it indexes your whole repository into a vector database and lets the agent ask for code by meaning ("find functions that handle user authentication") instead of reading directories or grepping for exact strings. It earns its setup cost on large codebases where Claude Code keeps missing the relevant files. On a small repo, an embedding provider plus a vector database is more infrastructure than the problem needs.

Highlights

• Hybrid retrieval — BM25 keyword scoring plus dense-vector similarity, so both exact identifiers and plain-language descriptions can match.
• Four tools — index_codebase, search_code, clear_index, and get_indexing_status.
• Incremental re-indexing — Merkle trees track what changed, so only modified files are re-indexed.
• AST-based chunking — code is split along its syntax tree, with automatic fallback to a character-based LangChain splitter.
• Pluggable embeddings and storage — OpenAI, VoyageAI, Gemini, or local Ollama for embeddings, and Milvus or Zilliz Cloud for the index.
• 14 languages out of the box — TypeScript, JavaScript, Python, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, Scala, and Markdown; add more extensions with CUSTOM_EXTENSIONS.

In an AI-assisted workflow

The README's Claude Code command uses OpenAI embeddings and a Zilliz Cloud database:

claude mcp add claude-context \
  -e OPENAI_API_KEY=sk-your-openai-api-key \
  -e MILVUS_ADDRESS=your-zilliz-cloud-public-endpoint \
  -e MILVUS_TOKEN=your-zilliz-cloud-api-key \
  -- npx @zilliz/claude-context-mcp@latest

Then drive it with the README's own prompts:

Index this codebase
Check the indexing status
Find functions that handle user authentication

To keep embeddings on your machine, the MCP package README shows a local Ollama setup, which "allows you to run embeddings locally without sending data to external services":

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "EMBEDDING_PROVIDER": "Ollama",
        "EMBEDDING_MODEL": "nomic-embed-text",
        "OLLAMA_HOST": "http://127.0.0.1:11434",
        "EMBEDDING_DIMENSION": "768",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

For background on how keyword and vector retrieval combine, and where a reranker fits, see our guide to hybrid search and reranking.

How it compares

Serena is the closest alternative, and the choice is about mechanism: Claude Context finds code by meaning through embeddings and hybrid search but has no editing tools and needs an embedding provider plus a vector database, while Serena uses language-server symbol knowledge (find symbols and references, symbol-level edits, renames) with no vector database at all. Context7 solves a different problem, serving third-party library docs rather than indexing your own repository, so the two stack well. Repomix is the low-infrastructure option when you'd rather hand the agent a whole-repo snapshot than query a persistent index.

Good to know

Claude Context is MIT licensed and maintained by Zilliz, with about 12.5k GitHub stars as of September 2026. It needs Node.js 20 or newer (the README says >= 20.0.0), an embedding provider, and Milvus or Zilliz Cloud; Docker isn't required. It's stdio only, with no hosted endpoint. The npm package @zilliz/claude-context-mcp was last published in June 2026 (v0.1.15), and the repo's last commit landed in July 2026; there are no GitHub Releases, and its git tags stop at v0.1.11 (April 2026). The same engine also ships as a VS Code extension, Semantic Code Search, and as @zilliz/claude-context-core for direct use.

Zilliz reports roughly 40% fewer tokens at equivalent retrieval quality, from its own evaluation. Two caveats: unless you use Ollama, your code goes to whichever embedding API you configure, and the README doesn't spell out Zilliz Cloud's free-tier limits. For setup scopes and passing env vars, see adding MCP servers to Claude Code, and for what else to install, the best MCP servers in 2026.