--- title: "claude-context" type: "tool" slug: "zilliztech-claude-context" canonical_url: "https://www.graphcanon.com/tools/zilliztech-claude-context" github_url: "https://github.com/zilliztech/claude-context" homepage_url: "https://github.com/zilliztech/claude-context/tree/master/docs" stars: 12078 forks: 894 primary_language: "TypeScript" license: "MIT" categories: ["ai-agents", "developer-tools"] tags: ["ai-coding", "embedding", "agentic-rag", "code-generation", "claude-code", "cursor", "agent", "code-search"] updated_at: "2026-07-07T18:32:33.257087+00:00" --- # claude-context > Code search MCP for Claude Code, integrating your entire codebase as context. Claude Context enhances AI coding agents like Claude Code with semantic code search, enabling deep understanding of large codebases by using a vector database to store and efficiently retrieve relevant information cost-effectively. ## Facts - Repository: https://github.com/zilliztech/claude-context - Homepage: https://github.com/zilliztech/claude-context/tree/master/docs - Stars: 12,078 · Forks: 894 · Open issues: 127 · Watchers: 53 - Primary language: TypeScript - License: MIT - Last pushed: 2026-06-22T09:35:11+00:00 ## Categories - [AI Agents](/categories/ai-agents.md) - [Developer Tools](/categories/developer-tools.md) ## Tags ai-coding, embedding, agentic-rag, code-generation, claude-code, cursor, agent, code-search ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [JavaGuide](/tools/snailclimb-javaguide.md) - Snailclimb/JavaGuide: 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发 (★ 156,863) - [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,298) - [dify](/tools/langgenius-dify.md) - Production-ready platform for agentic workflow development (★ 148,070) ## README (excerpt) ```text > 🆕 **Looking for persistent memory for Claude Code?** Check out [memsearch Claude Code plugin](https://github.com/zilliztech/memsearch#for-claude-code-users) — a markdown-first memory system that gives your AI agent long-term memory across sessions. ### Your entire codebase as Claude's context discord zilliztech/claude-context | Trendshift **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. --- ## 🚀 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](https://cloud.zilliz.com/signup?utm_source=github&utm_medium=referral&utm_campaign=2507-codecontext-readme) 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](https://platform.openai.com/api-keys). 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:** - Node.js >= 20.0.0 #### Configuration Use the command line interface to add the Claude Context MCP server: ```bash 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 ``` See the [Claude Code MCP documentation](https://docs.anthropic.com/en/docs/claude-code/mcp) 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: ```toml # 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.json` file. 2. Add the following configuration: ```json { "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" } } } } ``` 3. Save the file and restart G ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/zilliztech-claude-context`](/api/graphcanon/tools/zilliztech-claude-context) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_