Zen Multi-Model AI Collaboration
This Zen MCP Server by BeehiveInnovations provides AI-to-AI collaboration capabilities, enabling Claude to coordinate with multiple AI models (Gemini, OpenAI O3/O4, X.AI GROK) through conversation threading and cross-tool continuation. The implementation features 13 specialized tools including code analysis, debugging, test generation, consensus building, and pre-commit validation, with intelligent model selection in auto mode where Claude chooses the optimal model for each task. Built with Python and supporting both native APIs and OpenRouter integration, it enables multi-model workflows where different AI systems can question each other's approaches, build on previous conversations, and seamlessly switch between tools while preserving full context, making it valuable for complex development workflows requiring diverse AI perspectives and coordinated problem-solving.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-01.
Scan details: Circle-IR · 2026-09-01 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-01
- Updated
- 2026-09-01
Use via MCP
Resolve Zen Multi-Model AI Collaboration from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.