CodeAlive

You can connect your AI assistant to CodeAlive's MCP server to access powerful semantic code search and codebase interaction features. This MCP server enriches the context for AI agents across large codebases, helping you find relevant code faster, understand the bigger project picture, and reduce your development time and costs.

How to use

Use the MCP server to connect your AI client and perform three core actions: list your indexed data sources, search code semantically across the codebase, and consult the project for deeper insights. You typically start by configuring an MCP connection in your AI client, then issue natural language prompts like asking to locate authentication logic or to explain a payment flow. The server handles the underlying MCP protocol and returns structured results that your agent can incorporate into its responses.

How to install

Prerequisites: you need Python 3.11+ or Node.js for various client integrations depending on how you run the MCP server. You will also need a CodeAlive API key to authorize requests.

Install and run the MCP server locally to test or customize it before deploying to HTTPS. Follow these steps in sequence:

1. Clone the MCP server repository and enter the project directory.

2. Set up the local Python environment and install dependencies (if using the Python setup). 3. Install with pip in editable mode.

3. Start the local HTTP server or the local STDIO server depending on your preference. 4) Confirm the server health using the health endpoint or logs.

Concrete commands shown in the configurations below guide you through connecting clients or running the server locally.

Additional content

Configuration and usage details are described for multiple MCP clients to help you connect quickly. The server supports HTTP transport for remote access and STDIO transport for local host deployments. When using HTTP, you supply an Authorization header with your API key. For STDIO, you provide a containerized Docker command that runs the MCP server and forwards your API key via environment variables.

Security-wise, protect your API key and do not share it in public spaces. If you deploy self-hosted, ensure your endpoint is secured behind proper authentication and TLS.

Available tools

get_data_sources

List your indexed repositories and workspaces

codebase_search

Semantic search across your indexed codebase to find relevant files or code snippets

codebase_consultant

AI consultant with full project expertise to explain and reason about the codebase