PAL (Provider Abstraction Layer), formerly Zen MCP, connects your AI CLI to models from Gemini, OpenAI, OpenRouter, Azure, Grok, Ollama and others. Provides workflow tools for multi-model chat, code review, debugging, planning, consensus and CLI-to-CLI subagents via clink.
Connect
- 1Add the server to Codex
codex mcp add pal --env GEMINI_API_KEY=YOUR_GEMINI_API_KEY --env OPENAI_API_KEY=YOUR_OPENAI_API_KEY --env OPENROUTER_API_KEY=YOUR_OPENROUTER_API_KEY -- uvx --from git+https://github.com/BeehiveInnovations/pal-mcp-server.git pal-mcp-server
Configs are generated from the publisher's documented endpoint. Check their docs for plan requirements and scopes. New to this? Read the step-by-step tutorial.
Tools 12
chatthinkdeepplannerconsensuscodereviewprecommitdebugclinkanalyzerefactortestgensecauditThings to ask
- “Get a consensus from Gemini and GPT on this architecture”
- “Do a code review of my staged changes with o3”
- “Use thinkdeep to analyze this race condition”
- “Ask Codex via clink to hunt bugs in src/”