cmcp

Cool, adding this to my list of MCP CLIs: - https://github.com/apify/mcpc - https://github.com/chrishayuk/mcp-cli - https://github.com/wong2/mcp-cli - https://github.com/f/mcptools - https://github.com/adhikasp/mcp-client-cli - https://github.com/thellimist/clihub - https://github.com/EstebanForge/mcp-cli-ent - https://github.com/knowsuchagency/mcp2cli - https://github.com/philschmid/mcp-cli - https://github.com/steipete/mcporter - https://github.com/mattzcarey/cloudflare-mcp - https://github.com/assimelha/cmcp

After reading Cloudflare's Code Mode MCP blog post[1] I built CMCP[2] which lets you aggregate all MCP servers behind two mcp tools, search and execute. I do understand anthropic's Tool Search helps with mcp bloat, but it's limited only to claude. CMCP currently supports codex and claude but PRs are welcome to add more clients. [1]https://blog.cloudflare.com/code-mode-mcp/ [2]https://github.com/assimelha/cmcp

I built cmcp, a proxy that sits between your AI agent (Claude, Codex) and all your MCP servers. Instead of registering each server individually — which can add 100+ tool definitions to your agent's context — you register one proxy that exposes just 2 tools: search() and execute(). The agent writes TypeScript to discover and call tools: // search — find tools across all servers return tools.filter(t => t.name.includes("screenshot")); // execute — call tools with full type safety await chrome_devtools.navigate_page({ url: "https://example.com" }); const shot = await chrome_devtools.take_screenshot({ format: "png" }); return shot; Type declarations are auto-generated from each tool's JSON Schema, so the agent gets typed parameters for every tool. TypeScript is stripped via oxc and the JS runs in a sandboxed QuickJS engine (64 MB memory limit