CodeCortex

Install CodeCortex

Install instructions vary — visit the GitHub repository for the latest install command. Most MCP servers follow one of three patterns: npx -y <package> for Node, uvx <package> for Python, or docker run <image> for containerized servers.

Use CodeCortex with Claude Code

Once the server is on your machine, register it with Claude Code so the agent can call it like any other tool. The general pattern is:

claude mcp add rushikeshmore-codecortex -- <install-command>

After it's registered, run claude and ask anything that requires CodeCortex. Claude Code will negotiate the MCP handshake and surface the server's tools, prompts, and resources to the model automatically. See our Claude Code MCP guide for environment variables, scope flags, and credential handling.

What this server is for

CodeCortex sits in the knowledge & memory category. It's community-maintained — check the repo's last-commit date and open issues before depending on it in production. The full description from the source list:

Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client.

FAQ

Is CodeCortex free?

Yes — every MCP server in the ClawHire directory is open-source or freely available. Some servers proxy to paid APIs (you supply your own keys), but the server itself is free.

Does it work with Claude Desktop / Cursor / Windsurf?

If a client speaks the Model Context Protocol, it can use this server. The transport (stdio vs SSE vs HTTP) needs to match what the client supports, but the server itself is client-agnostic.

How do I report a bug or contribute?

Open an issue or PR on the GitHub repository.