Headroom vs Screencap: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Headroom and Screencap — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Headroom

Free

Headroom compresses tool outputs, logs, files, and RAG chunks before they reach the LLM, cutting 60-95% of tokens while preserving answers.

SmartCrusher Compression: Statistical JSON and array compression that removes 70-90% of tokens from tool outputs.
AST-Aware Code Compression: Uses tree-sitter analysis to compress source code while preserving structure.
Text & Log Compression: Shrinks search results, build logs, and diffs before they hit the model.
Compress-Cache-Retrieve: Reversible compression where originals are never deleted and the LLM can retrieve full content on demand.
Multiple Integrations: Ships as a Python package, a TypeScript package, an OpenAI/Anthropic-compatible HTTP proxy, and an MCP server.

Cost-Efficient Agents: Cut token spend on agents that read large tool outputs and logs.
RAG Pipelines: Compress retrieved chunks before they enter the prompt to fit more context.
Drop-In Proxy: Route OpenAI/Anthropic traffic through the proxy to compress payloads with no code changes.
MCP Workflows: Add compression and retrieval tools to MCP-based agent stacks.

Proteus Computer Use

Freemium

Local-first macOS screen recorder that captures, labels, and indexes team workflows so knowledge stays searchable and private.

Local-First Capture: Recordings live in ~/.screencap on your Mac and never leave unless you explicitly share them.
On-Device Task Segmentation: An on-device model breaks long recordings into labeled tasks like payroll runs, expense approvals, or CRM data entry.
Full-Text Search of Workflows: Every spoken word and on-screen moment is indexed so any past workflow can be surfaced months later by search.
Privacy-Enforced Recording: Password managers and banking apps are cut before a frame is written; email and chat are masked in real time.
MCP Context Snapshots: While recording, Screencap queries connected MCP servers to capture the exact Gusto/Attio/Linear/Notion record on screen inside the video.
Deliberate Sharing With PII Scrubbing: Every shared copy is scrubbed of names, secrets, and PII, and only the recordings you pick ever leave the machine.
Source-Available Codebase: The full capture engine, encryption, agent, and anonymizer are public on GitHub under PolyForm Noncommercial 1.0.0.

Team Onboarding: Assemble ordered collections of real workflow recordings so new teammates learn exactly how work is actually done.
Institutional Knowledge Capture: Preserve the tacit steps behind payroll runs, reconciliations, and quarterly reports as searchable video.
Ops Documentation: Replace stale wikis by pointing teammates at labeled task recordings that stay current with the real system.
Compliance-Sensitive Recording: Capture back-office work in banking, finance, and HR without leaking passwords, account balances, or PII.
Computer-Use Dataset Contribution: Optionally donate reviewed, scrubbed recordings to a public dataset for training open computer-use models.