Provides reversible context compression for AI agents, reducing token usage while preserving the ability to retrieve original content, and serves as an MCP server for integration with tools like GitHub Copilot and Claude Code.
Deterministic context compression for MCP agents, reducing token usage via 11 tools for prompts, history, shell output, file deltas, and code navigation without ML or GPU.
A local, zero-cloud MCP server for token and text compression. It provides tools to compress, auto-compress, measure, and decompress text using offline rules, lossless gzip packing, or a local Ollama semantic model.
A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.
Provides compression, retrieval, and statistics for local context-economy when interacting with GPT/Codex, enabling efficient token usage and exact recovery of compacted content.
