headroom git:20261014.b19aec4A

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---
name: headroom
description: Configure, use, or troubleshoot Headroom for local LLM-context compression with Codex, Claude Code, MCP clients, Python, TypeScript, or an OpenAI-compatible proxy. Use when the user explicitly mentions Headroom or asks to reduce coding-agent token use by compressing tool output, logs, files, JSON, or retrieved context. Do not trigger for ordinary prompt shortening or generic model-cost questions that do not involve Headroom.
license: Apache-2.0
metadata:
  source: https://github.com/headroomlabs-ai/headroom
  upstream-revision: f1bc260948c159549d6937e9c4d2cf969256f2bb
---

# Headroom

Help the user choose and operate the smallest Headroom setup that matches their goal. Headroom is separate software; loading this skill does not install or start it.

## Choose the integration

Use the user's existing environment and stated goal to select one mode:

| Goal | Preferred mode |
| --- | --- |
| Compress traffic for a Codex or Claude Code session | `headroom wrap codex` or `headroom wrap claude` |
| Claude Code inside VS Code | `headroom wrap vscode-claude` |
| Another coding agent (Grok, Copilot, Aider, OpenCode, Cline, Continue, Goose, and others) | `headroom wrap <agent>`; check `headroom wrap --help` for the installed list |
| Expose on-demand compression, retrieval, and stats | MCP server via `headroom mcp install` / `headroom mcp serve` |
| Route an existing OpenAI-compatible client without code changes | Local proxy on `127.0.0.1:8787` |
| Compress inside Python code | Python `compress()` API |
| Use the TypeScript SDK | TypeScript package plus a running Headroom proxy |
| Keep Headroom available across restarts | `headroom deploy` or a requested `headroom install` preset |

Prefer an on-demand wrapper or MCP setup for evaluation. Use persistent deployment only when the user asks for durable background operation.

## Install and verify

Headroom requires Python 3.10 or newer. For a host-level CLI in an isolated environment, the upstream default is:

```bash
uv tool install --python 3.13 "headroom-ai[all]"
headroom --version
headroom doctor
```

Install a smaller extra when the requested mode is narrow:

- MCP only: `uv tool install --python 3.13 "headroom-ai[mcp]"`
- Proxy: `uv tool install --python 3.13 "headroom-ai[proxy]"`
- Python library plus CLI: `pip install "headroom-ai[all]"`; framework adapters such as `[langchain]`, `[agno]`, `[strands]` and `[bedrock]` are separate extras
- TypeScript SDK: `npm install headroom-ai`; it ships no CLI and still requires a running proxy
- Container: `docker pull ghcr.io/headroomlabs-ai/headroom:latest`

Upgrade with `headroom update` (`--check` to only report), which detects pip, pipx or uv tool installs.

Do not install packages, start persistent services, or modify agent configuration unless the user's request authorizes that change. Never place provider keys or other credentials in commands, committed files, or chat output.

## Agent workflows

For a temporary agent session, run the matching wrapper and keep that process alive:

```bash
headroom wrap codex
headroom wrap claude
```

`headroom wrap claude` does more than route traffic. Tell the user before running it:

- It starts or reuses a local proxy and registers the Headroom MCP server (`--no-mcp` skips that).
- It registers the Serena code-navigation MCP server for the current project only. `--code-memory none` skips it; `--code-memory-scope user` makes it machine-wide.
- `--1m` keeps Claude Code's 1M context window, which is otherwise capped at 200k behind a custom base URL. `--memory` turns on cross-session memory.

Use `headroom unwrap <tool>` to restore durable settings created by wrapping; `unwrap claude` also removes the MCP registrations unless given `--keep-mcp`. Check configuration and savings with `headroom doctor`, `headroom perf`, and `headroom dashboard`.

For MCP, `headroom mcp install` registers the server in every detected agent; add `--agent claude` to limit it. When configuring by hand, point the host at the absolute path to the `headroom` executable if the host does not inherit the interactive shell `PATH`:

```toml
[mcp_servers.headroom]
command = "/absolute/path/to/headroom"
args = ["mcp", "serve"]
```

On Windows, locate it with `where headroom`. Do not assume the normal proxy exposes an HTTP MCP endpoint at `/mcp`. When HTTP MCP is specifically required, use `headroom mcp serve --transport http`, which defaults to `127.0.0.1:8788/mcp`. The `--direct` flag is deprecated and ignored.

For an OpenAI-compatible client, start the local proxy and point the client at it:

```bash
headroom proxy --port 8787
```

Keep the default loopback bind unless the user deliberately needs remote access. Verify the proxy before changing client configuration. On Anthropic `/v1/messages`, cache mode keeps the provider prompt-cache prefix stable and therefore skips automatic memory injection; use `--mode token` only when that injection is wanted. Output-token reduction is a separate opt-in (`HEADROOM_OUTPUT_SHAPER=1`), and `headroom output-savings` reports its estimated effect.

The `headroom proxy` command runs the Python proxy. Upstream also builds a Rust `headroom-proxy` binary, bundled in the Docker images, and plans to retire the Python request path in its favour. Treat that as a direction, not a current requirement, and check the release notes before relying on either.

## Persistent deployment

When the user explicitly wants a durable runtime, prefer the turnkey flow:

```bash
headroom deploy
headroom install status
```

`deploy` picks Docker when available, then the host scheduler (`launchd`, Task Scheduler, or cron), then a detached process, and it configures detected tools. It defaults to cache mode. Pass `--no-docker` to keep it native. For an explicit setup, use `headroom install apply`, which takes `--env KEY=VALUE` for variables the supervised runtime must see. Manage the lifecycle with `headroom install start`, `stop`, `restart`, or `remove`. Explain which provider or user configuration will change before applying a persistent profile, and preserve a clear undo path.

## Diagnose before changing

When Headroom is not working:

1. Check `headroom --version` and `headroom doctor`.
2. Confirm the installed extra covers the requested mode.
3. Resolve the actual executable path and verify the agent can see it.
4. Check whether port `8787` is already in use before starting another proxy.
5. For MCP, run `headroom mcp status`; a proxy is optional unless proxy-backed retrieval is intended.
6. Confirm savings with Headroom's stats or dashboard instead of assuming compression helped. Short or already-dense content may see little benefit.

Use the current upstream documentation for release-sensitive flags and platform details:

- Repository: https://github.com/headroomlabs-ai/headroom
- Installation: https://docs.headroomlabs.ai/docs/installation
- Quickstart: https://docs.headroomlabs.ai/docs/quickstart
- MCP: https://docs.headroomlabs.ai/docs/mcp
- Persistent installs: https://docs.headroomlabs.ai/docs/persistent-installs

This skill was prepared from upstream revision `f1bc260948c159549d6937e9c4d2cf969256f2bb`. Recheck the official documentation when commands or supported integrations may have changed.