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Unify multiple LLM providers, routing, and model collaboration in one local gateway.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "qiaomu-llm-mcp" yet — see the docs or source repo.
Help me design a local MCP gateway configuration that unifies OpenAI, Anthropic, and Gemini, with API key management, model aliases, task-based routing, and example configs.
A clear gateway setup plan, routing rules, and sample configuration files.
Design a model routing strategy for these tasks: code generation, long-form summarization, creative brainstorming, and low-cost bulk classification. Include suitable models, priorities, fallback logic, and cost considerations.
A task-based model selection and fallback plan balancing quality, reliability, and cost.
Design a multi-model collaboration workflow where one model proposes a solution, another challenges risks, and a third synthesizes the conclusion. Explain how to orchestrate calls and aggregate results through the MCP gateway.
An actionable multi-model discussion workflow with roles, call order, and result aggregation.
Route across multiple LLM providers with fallback, monitoring, and OpenAI-compatible APIs.
Route LLM completion requests to OpenAI-compatible providers through MCP tools.
Route prompts across LLM providers with policy-based orchestration and verification.
Delegate low-risk tasks to a cheaper model with main-agent review.
Route LLM requests across providers and orchestrate MCP tools with local privacy.
Build, debug, and manage software tasks with natural language across LLMs.