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Claude Context

Provides semantic code search and indexing using vector embeddings and AST-based code splitting, ena...

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Updated Sep 17, 2025
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Provides semantic code search and indexing using vector embeddings and AST-based code splitting, enabling natural language queries across codebases with automatic file filtering and support for multiple embedding providers and vector databases.
  1. Obtain a Zilliz Cloud API Key

    • Go to Zilliz Cloud Sign Up and sign up for a free account.
    • After signing up and logging in, navigate to your account dashboard.
    • Find your Personal API Key (labelled as “Personal Key”) and copy it. You will use this as your MILVUS_TOKEN.
    • (Optional) Locate the “Public Endpoint” for your database instance if your configuration or client requires MILVUS_ADDRESS.
  2. Obtain an OpenAI API Key

    • Navigate to OpenAI API Keys page.
    • Sign up for an OpenAI account if you don't have one, or log in.
    • Click “Create new secret key” and copy the generated key (it starts with sk-). This will be your OPENAI_API_KEY.
  3. Fill in the FastMCP Connection Interface

    • Click your platform’s “Install Now” or “Add MCP” button for the Claude Context integration.
    • In the FastMCP connection form that appears, fill in the required environment variables:
      • For OPENAI_API_KEY, paste your OpenAI API key.
      • For MILVUS_TOKEN, paste your Zilliz Cloud Personal API Key.
      • If required, for MILVUS_ADDRESS, paste your Zilliz Cloud project’s public endpoint.
    • Complete the setup by saving/applying the configuration.

You can now use Claude Context with your MCP-compatible client or platform. For more advanced environment variable options or troubleshooting, refer to the Environment Variables Guide or main documentation.

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