askbudi/roundtable

Stop copy-pasting between AI models. Roundtable AI is a local MCP server that lets your primary AI assistant delegate tasks to specialized models like Gemini, Claude, Codex, and Cursor. Solve complex engineering problems in parallel, directly from your IDE.
**Key Features:**
- **Context Continuity**: Shared project context across all sub-agents
- **Parallel Execution**: All agents work simultaneously
- **Model Specialization**: Right AI for each task (Gemini's 1M context, Claude's reasoning, Codex's implementation)
- **Zero Markup**: Uses your existing CLI tools and API subscriptions
- **26+ IDE Support**: Works with Claude Code, Cursor, VS Code, JetBrains, and more
Table of Contents
- Quick Start
- What is Roundtable AI
- Technical Architecture
- Why Multi-Agent vs Single AI
- Real-World Examples
- Installation
- IDE Integration
- Advanced Configuration
- Contributing
- License
Quick Start
**One-liner for Claude Code:**
**Try this multi-agent prompt in your IDE:**
What is Roundtable AI
Roundtable AI is a local Model Context Protocol (MCP) server that coordinates specialized AI sub-agents to solve complex engineering problems. Instead of manually switching between different AI tools, you delegate tasks from a single prompt in your IDE, and Roundtable manages the coordination, context sharing, and response synthesis.
Key Benefits
- **Context Continuity**: The primary agent provides shared, rich context to all sub-agents
- **Parallel Execution**: All agents work simultaneously, drastically reducing wait time
- **Model Specialization**: Use the right AI for each task - Gemini's 1M context for analysis, Claude's reasoning for logic, Codex for implementation
- **No Extra Cost**: Uses your existing CLI tools and API subscriptions with zero markup
- **Single Interface**: One prompt, multiple specialized responses, automatically synthesized
Technical Architecture
How It Works
1. **Context Continuity**: The initial prompt and relevant file/project context are packaged by the primary agent. The MCP server passes this "context bundle" to each sub-agent, ensuring all participants have the same ground truth without manual copy-pasting.
2. **Model Specialization**: Use the right model for the job. Leverage Gemini's 1M context for codebase analysis, Claude's reasoning for logic and implementation, and Codex's proficiency for code generation and reviews, all in one workflow.
3. **No Extra Cost**: Roundtable invokes the CLI tools you already have installed and configured. It uses your existing API keys and subscriptions. We add no markup. The cost is exactly what you would pay running the tools manually.
Why Multi-Agent vs Single AI
Because manual context-switching is slow, error-prone, and prevents deep analysis.
The Multi-Tab Workflow ❌
- Manually copy-paste code and context between different AI chats
- Each agent starts fresh, unaware of other conversations or files
- You wait for one agent to finish before starting the next
- You are responsible for merging disparate, often conflicting, advice
- High risk of pasting outdated code or incorrect context
The Roundtable Workflow ✅
- Delegate tasks from a single prompt in your IDE
- The primary agent provides shared, rich context to all sub-agents
- All agents work in parallel, drastically reducing wait time
- The final output automatically synthesizes the best insights from each model
- The entire workflow is a single, deterministic, and repeatable command
Real-World Examples
Each example includes real code, logs, and explicit delegation to specialized sub-agents. Copy the whole block and paste it into your IDE assistant.
1) Multi-Stack Debugging — Virtual War Room for Production Issues
json
{
"timestamp": "2024-09-24T10:05:21.123Z",
"level": "error",