Local MCP server for token optimization, providing tools to compress code/JSON, optimize prompts, and manage placeholder-based content redaction and hydration to reduce LLM token usage.
An MCP server that turns your machine or LAN of ollama nodes into a local token generator, enabling coding agents to delegate bounded processing tasks to local models and save cloud credits.
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 uses Claude 3.5 Sonnet to transform ordinary prompts into structured, professionally engineered instructions for any LLM. It enhances AI interactions by adding context, requirements, and structural clarity to raw user inputs.