docs: updated intro
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README.md
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# Zen MCP: Many Workflows. One Context.
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# Zen MCP: Many Workflows. One Context.
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[zen_web.webm](https://github.com/user-attachments/assets/851e3911-7f06-47c0-a4ab-a2601236697c)
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---
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### Now with **`clink`** – Connect Your CLIs Together
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Need Gemini (or another CLI agent) to join the conversation directly? The new [`clink`](docs/tools/clink.md) tool lets you **connect one CLI to another** ([gemini](https://github.com/google-gemini/gemini-cli) supported for now) so they can **plan, review, debate, and collaborate** inside the same context.
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Point `clink` at a CLI like Gemini with role presets (e.g., `planner`, `codereviewer`, `default`) and that agent will handle **web searches, file inspection, and documentation lookups** as a first-class participant in your workflow.
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---
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<div align="center">
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<div align="center">
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[zen_web.webm](https://github.com/user-attachments/assets/851e3911-7f06-47c0-a4ab-a2601236697c)
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### Your CLI + Multiple Models = Your AI Dev Team
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### Your CLI + Multiple Models = Your AI Dev Team
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**Use the 🤖 CLI you love:**
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**Use the 🤖 CLI you love:**
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@@ -23,16 +14,39 @@ Gemini · OpenAI · Anthropic · Grok · Azure · Ollama · OpenRouter · DIAL
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</div>
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</div>
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<br/>
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---
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**Why rely on one AI model when you can use them all?**
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## 🆕 Now with CLI-to-CLI Bridge
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The new **[`clink`](docs/tools/clink.md)** tool connects external AI CLIs directly into your workflow:
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- **Connect [Gemini CLI](https://github.com/google-gemini/gemini-cli)** (more CLIs coming soon) to collaborate alongside your primary AI
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- **Create Role presets** - `planner`, `codereviewer`, `default` for specialized tasks
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- **Full CLI capabilities** - Web search, file inspection, latest documentation lookups
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- **Seamless continuity** - Gemini participates as a first-class member with full conversation context
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```bash
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# Use consensus to decide on a feature, then hand off to Gemini for implementation
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"Use consensus to decide: dark mode or offline support next"
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"Continue with clink - implement the recommended feature"
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# Gemini receives the full debate context and starts coding immediately
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```
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**[Learn more about clink](docs/tools/clink.md)**
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---
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## Why Zen MCP?
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**Why rely on one AI model when you can orchestrate them all?**
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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
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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
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as [Cursor](https://cursor.com) or the [Claude Dev VS Code extension](https://marketplace.visualstudio.com/items?itemName=Anthropic.claude-vscode). **Zen MCP connects your favorite AI tool
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as [Cursor](https://cursor.com) or the [Claude Dev VS Code extension](https://marketplace.visualstudio.com/items?itemName=Anthropic.claude-vscode). **Zen MCP connects your favorite AI tool
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to multiple AI models** for enhanced code analysis, problem-solving, and collaborative development.
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to multiple AI models** for enhanced code analysis, problem-solving, and collaborative development.
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**True AI collaboration with conversation continuity** - Zen supports **conversation threading** so your
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### True AI Collaboration with Conversation Continuity
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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.
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Zen 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.
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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.
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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.
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