atlassian-labs/mcp-compressor

Compress all connected MCP into a single router MCP and save up to 99% on tokens

Context compression for MCP. Same upstream call, exact results recoverable.

A high-performance, token-efficient Model Context Protocol (MCP) gateway proxy. Avoids context bloat and eliminates multi-turn tool discovery latency by intercepting prompts and semantically injecting only the exact schemas the LLM needs.

Context compression for AI coding agents: compresses tool output before it enters the model, dedups repeats to 13-token refs. Claude Code, Cursor, Codex, Kiro, Zed, any MCP client. Rust, zero LLM calls.

Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

n2-QLN: Intelligent Tool Router & Semantic Search Layer for MCP. Connect 1,000+ tools through 1 interface. Prevent AI model confusion and maximize context window efficiency

The most compatible MCP CLI client. Supports: tools, resources, prompts, completions, async tasks, skills, stdio and streamable HTTP (MCP 2026-07-28 and 2025-11-25), persistent sessions, OAuth 2.1 with DCR, CIMD, client credentials, and ID-JAG, OS keychain, --json for code mode, grep for tool discovery, proxy for AI sandboxes, x402, and more.

Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.

MCP server that gets Claude to 97.9% (188/192) on a real coding benchmark at -80% active tokens and -83% wall time, vs 78.3% plain. Structural code navigation + persistent memory engine. Works with every MCP client.