Swarm Orchestrator
Provides autonomous Git management capabilities, including workflow automation, commit management, and branch handling.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Swarm Orchestratordebug the failing test in auth_test.py using SBFL"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
⚠️ DEPRECATED: Fully migrated to hermes agent.
Swarm Orchestrator v3.4
Turn your IDE into an Autonomous Engineering Team
Swarm Orchestrator is a Model Context Protocol (MCP) server that extends AI coding assistants like Antigravity, Cursor, and Claude Desktop with deterministic, algorithmic capabilities. Instead of relying purely on LLM reasoning, Vexorbis Swarm uses specialized workers—code analysis, fault localization, formal verification, and autonomous Git management—to deliver faster, more reliable results.
📖 Documentation
Getting Started | Concepts | Guides | Reference |
Related MCP server: projscan
🚀 Quick Start
Docker (Recommended)
git clone https://github.com/AgentAgony/swarm.git
cd swarm
docker compose up -d --buildConfigure Your IDE
Add the MCP server to your IDE's configuration (e.g., ~/.gemini/antigravity/mcp_config.json on Windows):
{
"mcpServers": {
"swarm-orchestrator": {
"command": "docker",
"args": ["exec", "-i", "swarm-mcp-server", "python", "server.py"]
}
}
}🔍 Tool Selection Guide
flowchart LR
Start([My Goal]) --> Q1{Type?}
Q1 -->|Find symbol by name| A["search_codebase(keyword_only=true)<br/>~1ms"]
Q1 -->|Find code by concept| B["search_codebase()<br/>~240ms"]
Q1 -->|Understand architecture| C["retrieve_context()<br/>~1-2s"]
Q1 -->|Debug failing tests| D["debug command<br/>Ochiai SBFL"]
style A fill:#2ecc71,color:#fff
style B fill:#3498db,color:#fff
style C fill:#9b59b6,color:#fff
style D fill:#e74c3c,color:#fff📜 License
MIT
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