First MCP server for data compression. 60x compression on docs, 30x on SQL, 20x on logs. Zero dependencies. Lossless. Auto-picks best algorithm. 7 tools for any AI agent.
mcp-compress
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
The first MCP server for data compression. Gives any AI agent the ability to compress, decompress, analyze, and store data.
**10,000+ MCP servers exist. Zero for compression. This is the first.**
Zero dependencies. Pure Node.js. Lossless round-trip. Auto-picks the best algorithm.
Benchmarks
Real results on real data types:
| Data Type | Original | Compressed | Ratio | Saved |
|-----------|----------|------------|-------|-------|
| Markdown docs (15KB) | 31.2 KB | 0.5 KB | **60.7x** | 98.4% |
| Repeated config (2KB) | 5.4 KB | 0.1 KB | **51.9x** | 98.1% |
| SQL query results (8KB) | 18.9 KB | 0.6 KB | **30.4x** | 96.7% |
| Log files (20KB) | 33.3 KB | 1.7 KB | **19.9x** | 95.0% |
| JSON API response (10KB) | 26.7 KB | 2.6 KB | **10.2x** | 90.2% |
| Time-series prices (4KB) | 20.5 KB | 3.0 KB | **6.9x** | 85.5% |
| CSV data (5KB) | 8.1 KB | 2.4 KB | **3.4x** | 70.5% |
Every compression is **lossless** — decompress returns the exact original, byte-for-byte.
Install
Claude Code
Add to ~/.claude/settings.json:
OpenClaw / Any MCP Client
Speaks MCP protocol over stdio. Works with any MCP-compatible AI agent.
From Source
Tools
7 tools available to any connected agent:
| Tool | What it does |
|------|-------------|
| compress | Compress text/JSON/CSV. Auto-picks best algorithm (gzip, brotli, deflate). Returns base64 + ratio. |
| decompress | Decompress back to original. Lossless round-trip verified. |
| analyze | Shannon entropy, compressibility rating, all algorithms compared, recommendation. |
| store | Compress and persist to disk with a key. Compressed key-value store for agents. |
| retrieve | Decompress and return stored data by key. |
| list | List all stored items with sizes and compression ratios. |
| stats | Total items stored, bytes saved, overall compression ratio. |
Usage Examples
**Compress a large API response:**
**Analyze before compressing:**
**Store data for later retrieval:**
**Check what you've stored:**
Why This Exists
- AI agents generate and consume massive amounts of text — API responses, code, docs, data
- Context windows are expensive. Compressed storage = more data in less space = lower cost.
- MCP is the standard protocol for AI agent tools. 10,000+ servers, none for compression.
- Auto-algorithm selection means the agent doesn't need to know anything about compression — it just works.