chopratejas/headroomMCPMCP Server

headroom

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

11.8kstars

770forks

Python

agentaianthropicclaude-codecompressioncontext-engineeringcontext-windowcursorfastapilangchainllmmcp

Quality signals

StaleNo testsNo CIThin docsNo licensePopular

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AI summary

Auto-generated overview of what this skill does and when to reach for it.

Compresses AI agent outputs, logs, and files by 60-95% before they reach the LLM without changing answers.

Use this when

Running daily coding agents and want to cut token costs
Debugging with long logs or tool outputs
Using multiple AI agents and need shared memory
Working with RAG chunks that exceed LLM context limits
Needing reversible compression to retrieve originals on demand

Don't use when

Only using a single provider’s built-in compaction
Working in a locked-down environment where local processes can’t run

Capabilities

Compresses JSON, code, logs, and text with 6 algorithms
Acts as a library, proxy, or MCP server
Shares memory across agents like Claude, Codex, Cursor
Reversible compression (CCR) stores originals locally
Auto-detects content type and selects the right compressor
Provides cross-agent memory and correction learning

InstallMCPRun via npx (Node)

Universal installANY TOOL

$ npx skillcity@latest chopratejas/headroom

Auto-detects the skill or MCP server in this repo and installs it for Claude Code, Codex, Cursor, Cline, OpenCode, Gemini CLI, Anti-Gravity, OpenClaw and Hermes.

Requires Node.js 18+ (ships with npx).

Or install manually

npx -y headroom

MCP Configuration

Add this to your claude_desktop_config.json

{
  "mcpServers": {
    "headroom": {
      "command": "npx",
      "args": [
        "-y",
        "headroom"
      ]
    }
  }
}

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Discover the toolingbehind modern intelligence

headroom