Claude Context is a semantic code search engine that indexes entire codebases and enables AI coding assistants to discover relevant code through intelligent vector search. Key features: - Semantic search across millions of lines of code to surface contextually relevant files and functions - Integration with Claude Code and other MCP-compatible AI agents - Vector database storage using Milvus/Zilliz Cloud for efficient embedding and retrieval - Cost-effective context management by selectively loading only pertinent code into AI context windows - Support for large-scale repositories without expensive full-directory ingestion

> 🆕 Looking for persistent memory for Claude Code? Check out memsearch Claude Code plugin — a markdown-first memory system that gives your AI agent long-term memory across sessions.

Your entire codebase as Claude's context

[](https://opensource.org/licenses/MIT) [](https://nodejs.org/) [](docs/) [](https://marketplace.visualstudio.com/items?itemName=zilliz.semanticcodesearch) [](https://www.npmjs.com/package/@zilliz/claude-context-core) [](https://www.npmjs.com/package/@zilliz/claude-context-mcp) [](https://twitter.com/zilliz_universe) [](https://deepwiki.com/zilliztech/claude-context)

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.

🧠 Your Entire Codebase as Context: Claude Context uses semantic search to find all relevant code from millions of lines. No multi-round discovery needed. It brings results straight into the Claude's context.

💰 Cost-Effective for Large Codebases: Instead of loading entire directories into Claude for every request, which can be very expensive, Claude Context efficiently stores your codebase in a vector database and only uses related code in context to keep your costs manageable.

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🚀 Demo

Model Context Protocol (MCP) allows you to integrate Claude Context with your favorite AI coding assistants, e.g. Claude Code.

Quick Start

Prerequisites

Get a free vector database on Zilliz Cloud 👈

Claude Context needs a vector database. You can sign up on Zilliz Cloud to get an API key.

Copy your Personal Key to replace your-zilliz-cloud-api-key in the configuration examples.

Get OpenAI API Key for embedding model

You need an OpenAI API key for the embedding model. You can get one by signing up at OpenAI.

Your API key will look like this: it always starts with sk-. Copy your key and use it in the configuration examples below as your-openai-api-key.

Configure MCP for Claude Code

System Requirements:

#### Configuration

Use the command line interface to add the Claude Context MCP server:

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

See the Claude Code MCP documentation for more details about MCP server management.

Other MCP Client Configurations

OpenAI Codex CLI

Codex CLI uses TOML configuration files:

1. Create or edit the ~/.codex/config.toml file.

2. Add the following configuration:

# IMPORTANT: the top-level key is mcp_servers rather than mcpServers.
[mcp_servers.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" }
Optional: override the default 10s startup timeout
startup_timeout_ms = 20000

3. Save the file and restart Codex CLI to apply the changes.

Gemini CLI

Gemini CLI requires manual configuration through a JSON file:

1. Create or edit the `~/.gemini/settings.js