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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.
Access multiple LLM providers through one encrypted OpenAI-compatible gateway.
Delegate low-risk tasks to a cheaper model with main-agent review.
Access multiple AI providers and local models securely through one gateway.
Run Llama models locally for private, offline AI assistance.
Build, debug, and manage software tasks with natural language across LLMs.
Turn existing APIs and databases into MCP tools for direct AI use.