Keep your coding agent. Make it cheaper.

CodeMesh is a context optimization layer for AI coding agents. It helps agents understand a codebase without repeatedly searching, opening and reading large amounts of source code, allowing them to work with more precise repository context and dramatically fewer unnecessary tokens.

CodeMesh works alongside the AI coding tools developers already use.

Claude.aiClaude CodeCursorDevin (formerly Windsurf)VS CodeChatGPTAny MCP client

What attaching CodeMesh looks like

The same exchange happens whichever tool you use, because they all reach CodeMesh over MCP: a question, the structural calls that answer it, and an answer. The tool pages below cover only what is specific to each one.

claude: connected to CodeMesh
‣ Where do we handle token refresh, and who calls it?
⚙ search-code query: "token refresh"
→ server/auth/tokens.ts:118  score 0.94
→ engine/src/auth.rs:47  score 0.81
⚙ query-context MATCH (c:CodeFunction)-[:CALLS]->(f) WHERE f.name = 'refreshTokens'
→ 3 callers
refreshTokens() in server/auth/tokens.ts rotates the token and revokes the whole family if a spent one is replayed. Called from the token endpoint, the daemon's retry path, and auth.rs on a 401.

No new coding workflow to learn. CodeMesh becomes the context layer underneath your existing AI development workflow.

Connect your repository to CodeMesh

Install the extension, open a repository, and connect the coding agent you already use.

Connect My RepositorySee the Benchmark