MCP server that delegates mechanical tasks like summarization, classification, extraction, and drafting to a local Llama.cpp LLM, serving as a cost-optimization layer while Claude handles reasoning and quality control.
An MCP server that allows Claude Code to offload mechanical tasks such as summarization, classification, and drafting to a local LLM, reducing API costs while keeping Claude in control of complex reasoning and quality review.
An MCP server that offloads light LLM work from Claude to a model you control, such as a local LLM or any OpenAI-compatible provider, saving frontier-model quota on non-critical tasks.
An MCP server that reduces token usage by lazily loading skills and tools only when needed, and routing repetitive subtasks to ML backends instead of the LLM.
Unified MCP server for querying multiple LLM providers (Gemini, OpenAI, Anthropic, etc.) with advanced routing, cost optimization, and fallback resilience.
