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Route prompts across LLM providers with policy-based orchestration and verification.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "llm-gateway-mcp" yet — see the docs or source repo.
Design a declarative routing policy for llm-gateway-mcp: send everyday Q&A to a low-cost model, code generation to a high-quality model, and require verification for sensitive tasks. Include example configuration.
A clear routing policy and sample configuration covering model selection, triggers, and verification rules.
I want to self-host llm-gateway-mcp. Give me deployment steps, required environment variables, common LLM provider integration methods, and production security recommendations.
An actionable deployment guide with integration setup, operational notes, and security hardening advice.
Design a multi-role workflow for llm-gateway-mcp: one model drafts the answer, another independently reviews and corrects it. Provide the workflow description and prompt templates.
A multi-role orchestration plan with role responsibilities, execution order, and reusable prompt templates.
Route LLM requests across providers and orchestrate MCP tools with local privacy.
Route LLM completion requests to OpenAI-compatible providers through MCP tools.
Proxy and manage multiple MCP servers through one secure unified interface.
Access multiple LLM providers through one encrypted OpenAI-compatible gateway.
Turn OpenAPI specs into MCP servers for LLM access to REST APIs.
Route across multiple LLM providers with fallback, monitoring, and OpenAI-compatible APIs.