An MCP server that exposes token-optimization pipeline functions as tools, enabling MCP-compatible hosts to reduce token usage in requests before they are forwarded to an Anthropic-compatible backend.
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.
MCP server for deterministic context preflight, token counting, and credential redaction for coding agents, with a free local tier up to 12,000 characters and paid HTTP fallback for larger inputs.
MCP server that minimizes LLM token usage by compressing, summarizing, filtering, chunk-referencing, and pruning large context before it reaches the model, with heuristic or local-SLM smart actions, caching, and token counting.