{"repo":"RagavRida/mmcp","free":true,"listed":false,"github":"https://github.com/RagavRida/mmcp","clone":"git clone https://github.com/RagavRida/mmcp.git","description":"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-core | pip install mmcp-core","language":"TypeScript","stars":33,"topics":["agent-coordination","ai","ai-agents","anthropic","cli","context-protocol","dag","deepseek","gemini","llm"],"license":"MIT","category":"ai-agents","readme_excerpt":"🔀 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. Your Task Domain Detected Model Selected Domain Score ----------- ---------------- --------------- ------------- \"Write a Python API with auth\" code generation GPT-4o 0.96 \"Debug this React component\" code review Claude Sonnet 0.91 \"Prove this calculus theorem\" math reasoning DeepSeek R1 0.92 \"Write a blog post about AI\" creative writing Claude Sonnet 0.90 \"Find SQL injection in this code\" security Claude Opus 0.94 \"Summarize this in one line\" summarization Haiku 0.88 GPT-4o scores 96% on code but 44% on math. DeepSeek scores 92% on math but 60% on code. MMCP knows the difference and routes accordingly. How Domain Routing Works Auto-Update When Models Change Per-Model Domain Profile You don't pick the model. You describe the task. MMCP learns which model wins at which domain. 🏗️ How It Works Every node produces a Context Envelope — an inspectable, serializable record. The full DAG is your audi","default_branch":null,"files":null,"tree":[],"storefront":"/r/RagavRida","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/RagavRida/mmcp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}