🔀 MMCP — Multi-Model Collaboration Pipeline Orchestrate AI models as a coordinated DAG. RL routing · Multi-verifier voting · Agent mesh · Self-improving. MCP standardizes tool use for a single model. MMCP standardizes context flow between models. ⚡ 30-Second Quick Start That's it. Type a task, MMCP picks the best model + pattern automatically. 🧠 Domain-Aware RL Routing — The Right Model for Every Task MMCP doesn't just pick a model — it learns per domain which model performs best, then routes automatically. When models get updated, benchmark results feed back into the router. | Y
| Stars | 32 |
| Forks | 0 |
| Language | TypeScript |
| Category | MCP 服务器 |
| License | MIT |
| Quality Score | 34.25/100 |
| Last Updated | 2026-06-03 |
| Created | 2026-02-28 |
| Platforms | cli, gemini, mcp, node |
| Est. Tokens | ~48k |
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mmcp is Multi-Model Collaboration Pipeline — orchestrate AI models as a DAG. RL routing, multi-verifier voting, agent mesh, self-improving. Works with OpenAI, Anthropic, Gemini, DeepSeek. npm install mmcp-cor. It is categorized as a MCP 服务器 with 32 GitHub stars.
mmcp is primarily written in TypeScript. It covers topics such as agent-coordination, ai, ai-agents.
You can find installation instructions and usage details in the mmcp GitHub repository at github.com/RagavRida/mmcp. The project has 32 stars and 0 forks, indicating an active community.
mmcp is released under the MIT license, making it free to use and modify according to the license terms.