pal-mcp-server

# PAL MCP: Many Workflows. One Context. <div align="center"> <em>Your AI's PAL – a Provider Abstraction Layer</em><br /> _{<a href="docs/name-change.md">Formerly known as Zen MCP</a>} [PAL in action](https://github.com/user-attachments/assets/0d26061e-5f21-4ab1-b7d0-f883ddc2c3da) 👉 **[Watch more examples](#-watch-tools-in-action)** ### Your CLI + Multiple Models = Your AI Dev Team **Use the 🤖 CLI you love:** [Claude Code](https://www.anthropic.com/claude-code) · [Gemini CLI](https://github.com/google-gemini/gemini-cli) · [Codex CLI](https://github.com/openai/codex) · [Qwen Code CLI](https://qwenlm.github.io/qwen-code-docs/) · [Cursor](https://cursor.com) · _and more_ **With multiple models within a single prompt:** Gemini · OpenAI · Anthropic · Grok · Azure · Ollama · OpenRouter · DIAL · On-Device Model </div> --- ## 🆕 Now with CLI-to-CLI Bridge The new **[`clink`](docs/tools/clink.md)** (CLI + Link) tool connects external AI CLIs directly into your workflow: - **Connect external CLIs** like [Gemini CLI](https://github.com/google-gemini/gemini-cli), [Codex CLI](https://github.com/openai/codex), and [Claude Code](https://www.anthropic.com/claude-code) directly into your workflow - **CLI Subagents** - Launch isolated CLI instances from _within_ your current CLI! Claude Code can spawn Codex subagents, Codex can spawn Gemini CLI subagents, etc. Offload heavy tasks (code reviews, bug hunting) to fresh contexts while your main session's context window remains unpolluted. Each subagent returns only final results. - **Context Isolation** - Run separate investigations without polluting your primary workspace - **Role Specialization** - Spawn `planner`, `codereviewer`, or custom role agents with specialized system prompts - **Full CLI Capabilities** - Web search, file inspection, MCP tool access, latest documentation lookups - **Seamless Continuity** - Sub-CLIs participate as first-class members with full conversation context between tools ```bash # 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 ``` 👉 **[Learn more about clink](docs/tools/clink.md)** --- ## Why PAL MCP? **Why rely on one AI model when you can orchestrate them all?** A Model Context Protocol server that supercharges tools like [Claude Code](https://www.anthropic.com/claude-code), [Codex CLI](https://developers.openai.com/codex/cli), and IDE clients such as [Cursor](https://cursor.com) or the [Claude Dev VS Code extension](https://marketplace.visualstudio.com/items?itemName=Anthropic.claude-vscode). **PAL MCP connects your favorite AI tool to multiple AI models** for enhanced code analysis, problem-solving, and collaborative development. ### True AI Collaboration with Conversation Continuity PAL supports **conversation threading** so your CLI can **discuss ideas with multiple AI models, exchange reasoning, get second opinions, and even run collaborative debates between models** to 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. <details> <summary><b>Reasons to Use PAL MCP</b></summary> A typical workflow with Claude Code as an example: 1. **Multi-Model Orchestration** - Claude coordinates with Gemini Pro, O3, GPT-5, and 50+ other models to get the best analysis for each task 2. **Context Revival Magic** - Even after Claude's context resets, continue conversations seamlessly by having other models "remind" Claude of the discussion 3. **Guided Workflows** - Enforces systematic investigation phases that prevent rushed analysis and ensure thorough code examination 4. **Extended Context Windows** - Break Claude's limits by delegating to Gemini (1M tokens) or O3 (200K tokens) for massive codebases 5. **True Conversation Continuity** - Full context flows across tools and models - Gemini remembers what O3 said 10 steps ago 6. **Model-Specific Strengths** - Extended thinking with Gemini Pro, blazing speed with Flash, strong reasoning with O3, privacy with local Ollama 7. **P