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added doc MCP server information
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title: MCP Server
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description: Connect AI applications to Maestro's documentation knowledge base using the Model Context Protocol.
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icon: plug
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---
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# MCP Server
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Maestro provides a hosted MCP (Model Context Protocol) server that allows AI applications to search and retrieve information from the Maestro documentation.
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## Overview
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The MCP server exposes a `SearchMaestro` tool that enables AI assistants to find relevant documentation, code examples, API references, and guides from the Maestro knowledge base.
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**MCP Server URL:**
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```
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https://docs.runmaestro.ai/mcp
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```
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## Available Tools
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### SearchMaestro
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Search across the Maestro knowledge base to find relevant information.
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**Use this tool when you need to:**
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- Answer questions about Maestro features and functionality
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- Find specific documentation pages
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- Understand how features work
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- Locate implementation details and code examples
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**Returns:**
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- Contextual content with titles
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- Direct links to documentation pages
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## Connecting AI Applications
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### Claude Desktop
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Add the MCP server to your Claude Desktop configuration (`claude_desktop_config.json`):
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```json
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{
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"mcpServers": {
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"maestro": {
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"url": "https://docs.runmaestro.ai/mcp"
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}
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}
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}
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```
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### Claude Code
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Add to your Claude Code MCP settings:
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```json
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{
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"mcpServers": {
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"maestro": {
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"url": "https://docs.runmaestro.ai/mcp"
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}
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}
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}
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```
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### Other MCP-Compatible Applications
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Any application that supports the Model Context Protocol can connect using the server URL:
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```
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https://docs.runmaestro.ai/mcp
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```
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## Example Queries
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Once connected, your AI assistant can use the `SearchMaestro` tool to answer questions like:
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- "How do I set up Auto Run in Maestro?"
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- "What keyboard shortcuts are available?"
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- "How does Group Chat work?"
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- "How do I configure git worktrees?"
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- "What AI agents does Maestro support?"
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## Technical Details
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- **Protocol**: Model Context Protocol (MCP)
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- **Transport**: HTTP/HTTPS
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- **Authentication**: None required (public read-only access)
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- **Rate Limits**: Standard API rate limits apply
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## Related Resources
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- [Model Context Protocol Documentation](https://modelcontextprotocol.io/)
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- [Maestro Documentation](https://docs.runmaestro.ai)
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- [GitHub Repository](https://github.com/pedramamini/Maestro)
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