Zen MCP

Your CLI + Multiple Models = Your AI Dev Team

With multiple models within a single prompt:
Gemini · OpenAI · Anthropic · Grok · Azure · Ollama · OpenRouter · DIAL · On-Device Model

# Codex spawns Codex subagent for isolated code review in fresh context clink with codex codereviewer to audit auth module for security issues # Subagent reviews in isolation, returns final report without cluttering your context as codex reads each file and walks the directory structure # Consensus from different AI models → Implementation handoff with full context preservation between tools Use consensus with gpt-5 and gemini-pro to decide: dark mode or offline support next Continue with clink gemini - implement the recommended feature # Gemini receives full debate context and starts coding immediately

Why rely on one AI model when you can orchestrate them all?

True AI Collaboration with Conversation Continuity

PAL supportsconversation threadingso your CLI candiscuss ideas with multiple AI models, exchange reasoning, get second opinions, and even run collaborative debates between modelsto help you reach deeper insights and better solutions.

Your CLI always stays in control but gets perspectives from the best AI for each subtask. Context carries forward seamlessly across tools and models, enabling complex workflows like: code reviews with multiple models → automated planning → implementation → pre-commit validation.

You're in control.Your CLI of choice orchestrates the AI team, but you decide the workflow. Craft powerful prompts that bring in Gemini Pro, GPT 5, Flash, or local offline models exactly when needed.

A typical workflow with Claude Code as an example:
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Multi-Model Orchestration- Claude coordinates with Gemini Pro, O3, GPT-5, and 50+ other models to get the best analysis for each task

Context Revival Magic- Even after Claude's context resets, continue conversations seamlessly by having other models "remind" Claude of the discussion

Guided Workflows- Enforces systematic investigation phases that prevent rushed analysis and ensure thorough code examination

Extended Context Windows- Break Claude's limits by delegating to Gemini (1M tokens) or O3 (200K tokens) for massive codebases

True Conversation Continuity- Full context flows across tools and models - Gemini remembers what O3 said 10 steps ago

Model-Specific Strengths- Extended thinking with Gemini Pro, blazing speed with Flash, strong reasoning with O3, privacy with local Ollama

Professional Code Reviews- Multi-pass analysis with severity levels, actionable feedback, and consensus from multiple AI experts

Smart Debugging Assistant- Systematic root cause analysis with hypothesis tracking and confidence levels

Automatic Model Selection- Claude intelligently picks the right model for each subtask (or you can specify)

Vision Capabilities- Analyze screenshots, diagrams, and visual content with vision-enabled models

Local Model Support- Run Llama, Mistral, or other models locally for complete privacy and zero API costs

Bypass MCP Token Limits- Automatically works around MCP's 25K limit for large prompts and responses

The Killer Feature:When Claude's context resets, just ask to "continue with O3" - the other model's response magically revives Claude's understanding without re-ingesting documents!

Example: Multi-Model Code Review Workflow

All within a single conversation thread! Gemini Pro in step 11knowswhat was recommended by O3 in step 7! Taking that context and review into consideration to aid with its final pre-commit review.

Think of it as Claude CodeforClaude Code.This MCP isn't magic. It's justsuper-glue.

Remember:Claude stays in full control — butYOUcall the shots. PAL is designed to have Claude engage other models only when needed — and to follow through with meaningful back-and-forth.You'rethe one who crafts the powerful prompt that makes Claude bring in Gemini, Flash, O3 — or fly solo. You're the guide. The prompter. The puppeteer.