How does Claude Context differ from plain grep or keyword search?
It uses semantic search (vector embeddings) to retrieve code based on meaning, not exact keyword matches, catching relevant code that keyword search would miss.

@zilliztech
Basic information
Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": [
"@zilliz/claude-context-mcp@latest"
],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}Index a codebase directory to enable semantic search using a configurable code splitter. ⚠️ **IMPORTANT**: - You MUST provide an absolute path to the target codebase. ✨ **Usage Guidance**: - This tool is typically used when search fails due to an unindexed codebase. - If indexing is attempted on an already indexed path, and a conflict is detected, you MUST prompt the user to confirm whether to proceed with a force index (i.e., re-indexing and overwriting the previous index).
Search the indexed codebase using natural language queries within a specified absolute path. ⚠️ **IMPORTANT**: - You MUST provide an absolute path. 🎯 **When to Use**: This tool is versatile and can be used before completing various tasks to retrieve relevant context: - **Code search**: Find specific functions, classes, or implementations - **Context-aware assistance**: Gather relevant code context before making changes - **Issue identification**: Locate problematic code sections or bugs - **Code review**: Understand existing implementations and patterns - **Refactoring**: Find all related code pieces that need to be updated - **Feature development**: Understand existing architecture and similar implementations - **Duplicate detection**: Identify redundant or duplicated code patterns across the codebase ✨ **Usage Guidance**: - If the codebase is not indexed, this tool will return a clear error message indicating that indexing is required first. - You can then use the index_codebase tool to index the codebase before searching again.
Clear the search index. IMPORTANT: You MUST provide an absolute path.
Get the current indexing status of a codebase. Shows progress percentage for actively indexing codebases and completion status for indexed codebases.
Claude Context is an MCP server that provides semantic code search and context retrieval for large codebases. It indexes your entire codebase using a vector database (Zilliz Cloud) and allows developers to query code with natural language instead of keyword matching.
Configure the server with your codebase path, Zilliz Cloud credentials, and optional file extension/ignore patterns. Then use MCP to send semantic search queries (e.g., "find functions that handle user authentication") and receive relevant code chunks in response.
It uses semantic search (vector embeddings) to retrieve code based on meaning, not exact keyword matches, catching relevant code that keyword search would miss.
Yes. It integrates with Zilliz Cloud for scalable vector search, and incremental indexing ensures only changed files are re-processed.
Claude Context uses Merkle trees to detect changes and performs incremental re-indexing, so only the modified portions are updated without a full rebuild.
You can configure which file extensions to include, set ignore patterns for directories or files, and choose the embedding model used for vectorization.

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