Headroom

What is Headroom?

Headroom is a context optimization layer that sits between an AI agent or app and its model provider. It compresses tool outputs, database results, file reads, retrieved documents and API responses so the model receives fewer tokens, which lowers cost and speeds up replies. Different content gets different treatment: JSON arrays keep errors and anomalies, build logs keep failures and drop passing noise, git diffs keep change hunks, and images are resized by a router. Source code compression is AST-aware and off by default. You can run Headroom as a transparent proxy with no code changes for clients such as Claude Code, Cursor or the OpenAI SDK, or call a compress function from Python or TypeScript. A reversible mode lets the model retrieve the original data. The open-source edition is free under Apache 2.0, while Headroom Enterprise adds automatic model routing, prompt-injection stripping, SSO and a team savings dashboard, with the first three months free on a 12-month plan.

Use cases

• Cut token use in coding agents
• Compress logs and tool output
• Shrink RAG chunks before prompting
• Route requests to cheaper models
• Share compressed context between agents
• Reduce image tokens for vision models

Who it's for

• AI engineers
• Developers using coding agents
• Engineering teams

Why use Headroom

• Sending fewer tokens to the model lowers API spend for agents that read large files, logs and search results.
• Proxy mode requires no code changes, so existing tools like Claude Code or Cursor can route through it.
• Reversible compression means the model can still fetch the original data when it needs detail.
• Everything in the open-source repository stays under Apache 2.0, so individuals can use it without a license fee.
• Teams can add Enterprise routing and security features later without changing the compression layer.

Headroom features

• Transparent proxy for any LLM client
• Python and TypeScript compress() functions
• SmartCrusher statistical JSON compression
• AST-aware code compression via tree-sitter
• Log, diff and search result compressors
• Image compression for vision models
• Reversible compression with Compress-Cache-Retrieve
• Cache optimization for provider KV caches
• Persistent memory and SharedContext for agents
• Rule-based model routing (opt-in)

Headroom integrations

• OpenAI
• Anthropic
• Google
• Bedrock
• LiteLLM
• Vercel AI SDK
• LangChain
• LangGraph
• Agno
• Claude Code
• Cursor
• MCP

How to get started with Headroom

1. Install Headroom with pip, npm or Docker.
2. Start the proxy and point your agent or SDK at it, or call compress() on your messages in Python or TypeScript.
3. Headroom routes each piece of content to the right compressor and forwards a smaller prompt to your LLM provider.
4. Check the reported tokens saved and, if you want, turn on opt-in features such as code compression or model routing.

Headroom limitations

• Savings depend on how repetitive the content is
• Source code compression is opt-in and disabled by default
• The open-source edition is built for one developer on one laptop
• Automatic model routing, injection stripping and SSO are Enterprise only
• Enterprise pricing is not published; contact the team

Headroom pricing

Headroom is open source, so you can use and self-host it for free.

Headroom plans

• Open source

  Free

  • Compression of tool outputs and logs
  • Tool search on Anthropic requests
  • Rule-based model routing
  • Community support via GitHub and Discord

• Enterprise

  Custom

  first 3 months free on a 12-month plan

  • Tool search for every model
  • Automatic model routing
  • Prompt injection stripping
  • SSO and org-wide savings dashboard

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

Headroom alternatives

The main Headroom alternatives listed on Debuly are LLMLingua, LiteLLM, Portkey, Helicone, Blackbox AI and LeanCTX. The table compares pricing and platforms; order is A–Z.

1. 

   Blackbox AI

   Inference platform with one OpenAI-compatible endpoint for 300+ open and closed models, encrypted connections, and dedicated enterprise deployments.

   Developer platformsCodingAutomation and agents
   Contact salesVisit Blackbox AI (official site)
2. 

   Helicone

   Open-source LLM observability and AI gateway that logs requests, tracks cost and latency, and routes to 100+ models through one API.

   Developer platformsCoding
   FreemiumVisit Helicone (official site)
3. 

   LeanCTX

   Open-source context gateway that trims what AI coding tools read, caches repeat reads and logs what each agent was given.

   Developer platformsCodingAutomation and agents
   FreemiumVisit LeanCTX (official site)
4. 

   LiteLLM

   Open-source AI gateway and Python SDK that gives one OpenAI-format API to 100+ LLM providers, with keys, budgets and cost tracking.

   Developer platformsCodingAutomation and agents
   Open sourceVisit LiteLLM (official site)
5. LL

   LLMLingua

   Microsoft research toolkit for compressing long LLM prompts, cutting token counts, API cost and latency with little loss of meaning.

   Developer platformsResearch and searchAutomation and agents
   Open sourceVisit LLMLingua (official site)
6. 

   Portkey

   AI gateway with observability, guardrails, caching and prompt management for teams running LLM apps in production.

   Developer platformsAutomation and agents
   FreemiumVisit Portkey (official site)

Headroom FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

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