Product comparison · reviewed August 16, 2026
One local-first history for approved agents on macOS, Windows, and Linux. A side-by-side look at scope, data control, platform support, and extensibility—without pretending one product is best for everyone.
Same criteria
Both products are evaluated against the same feature and deployment questions.
Trade-offs included
ChatGPT Computer History's strengths are shown alongside Screenpipe's.
No winner score
The right choice depends on the job, risk model, and operating environment.
The practical differences
Start with the criteria that can actually change your decision. Marketing category labels are less useful than concrete operating constraints.
screenpipe exposes the history over a documented REST API and an MCP server, so the agent you use tomorrow reads the same memory you built today.
OpenAI documents that Computer History is unavailable with API keys or Amazon Bedrock.
screenpipe publishes its source on GitHub so the capture, storage, and upload paths can be reviewed line by line.
Both products lead with the accessibility tree because it is cheap and accurate. screenpipe adds the pixels and the sound when the text alone is not enough.
Side by side
Capabilities can change. Treat this as an evaluation starting point and verify purchase-critical requirements with each vendor.
| Criterion | Screenpipe | ChatGPT Computer History |
|---|---|---|
| Works Withscreenpipe exposes the history over a documented REST API and an MCP server, so the agent you use tomorrow reads the same memory you built today. | Any harness: Claude Code, Codex, Cursor, Claude Desktop, custom agents | ChatGPT desktop app and Codex only |
| AI Provider ChoiceOpenAI documents that Computer History is unavailable with API keys or Amazon Bedrock. | Anthropic, OpenAI, Google, Ollama, and OpenAI-compatible endpoints | OpenAI only |
| Published Sourcescreenpipe publishes its source on GitHub so the capture, storage, and upload paths can be reviewed line by line. | Source-available under the Screenpipe Commercial License | Not available |
| Platform Support | Mac, Windows, Linux | macOS only |
| What Is CapturedBoth products lead with the accessibility tree because it is cheap and accurate. screenpipe adds the pixels and the sound when the text alone is not enough. | Accessibility tree, screen frames with OCR fallback, microphone and system audio | Accessibility interaction events: clicks, typing, shortcuts, app switches |
| Audio and Meetings | 24/7 mic + system audio, meeting transcripts, speaker labels | Not available |
| Where Processing Happens | Capture, indexing, and local search run on device; cloud AI and sync are user-configured | Temporary event files processed on OpenAI servers to generate memories |
| Raw History Storage | Local SQLite database; optional sync or customer-owned storage for teams | Event files kept on the Mac for up to 48 hours, memories stored locally unencrypted |
| Developer API | REST API + MCP server + direct SQL | Not documented, memories are consumed inside ChatGPT and Codex |
| Automation | Scheduled tasks written in markdown, triggered by schedule, events, or captured context | Suggests skills and automations inside ChatGPT |
| Team Controls | Admin policy, per-device controls, customer-owned storage | Admin grants workspace access, then each member opts in |
| Plan Requirement | Free tier, with paid individual and team plans | ChatGPT Pro, Business, or Enterprise |
Evidence review
Reviewed on August 16, 2026. The comparison below uses OpenAI's Computer History documentation and screenpipe's published product architecture so the trade-offs are traceable to primary sources.
OpenAI documents that Computer History records interaction events and does not capture screen or audio, that event files are deleted after 48 hours, that OpenAI processes those files on its servers to generate memories stored locally, and that the feature requires Memories and is unavailable with API keys or Amazon Bedrock.
The source repository documents cross-platform screen and audio capture, accessibility extraction with OCR fallback, local storage, the local API, MCP, and data controls.
The security architecture describes local-only and optional cloud data paths, endpoint controls, and enterprise deployment boundaries.
| Decision criterion | ChatGPT Computer History | Screenpipe | What it means |
|---|---|---|---|
| Who can read the memory | ChatGPT and Codex, inside OpenAI's own clients | Any agent over MCP or REST, plus direct SQL | If you have standardized on ChatGPT, Computer History is the shortest path. If you run more than one harness, or expect to switch, a shared history is worth more than a built-in one. |
| Capture scope | Accessibility interaction events only, no screen or audio | Accessibility tree first, screen frames with OCR fallback, mic and system audio | A narrower surface is the safer default. It is also the reason Computer History cannot answer questions about what was on the screen or what was said on a call. |
| Where the raw work leaves the machine | Temporary event files are processed on OpenAI servers to build memories | Capture, indexing, and local search run on device; cloud features are user-configured | Both store useful state locally. screenpipe also publishes the capture path and supports a local-only configuration; optional cloud features have separate data paths. |
| Team deployment | Admin grant plus per-member opt in, macOS only, vendor-hosted processing | Admin policy, per-device controls, storage in a bucket the customer owns, Mac, Windows, and Linux | OpenAI solves consent well. screenpipe additionally solves where the data lives and which machines are covered. |
Decision guide
Choose ChatGPT Computer History if
Choose Screenpipe if
Context
OpenAI and screenpipe agree on the premise: an assistant that cannot see how you actually work will keep asking you to explain yourself. Computer History answers that by turning macOS accessibility events into memories for ChatGPT and Codex. screenpipe answers it by building the history as its own layer, then handing it to whatever agent you point at it. The difference shows up the moment you want a second tool to use the same context. Computer History is a feature of one assistant. screenpipe is a place your work history lives.
Computer History is documented as part of the ChatGPT desktop app, it powers ChatGPT and Codex, and OpenAI states it is unavailable with API keys or Amazon Bedrock. That is a reasonable product decision and a real lock-in cost: the memory you accumulate is only worth what OpenAI's clients can do with it. screenpipe publishes a REST API and an MCP server over the same database, so Claude Code, Codex, Cursor, Claude Desktop, an internal agent, or a plain SQL query can use one history. Model choice is separate from capture: use Anthropic, OpenAI, Google, an OpenAI-compatible endpoint, or keep inference on device with Ollama. When the best model changes, your memory does not have to move.
Computer History keeps generated memory files on the Mac, and OpenAI says temporary event files are deleted after 48 hours and are not used for training. But the step that turns events into memories runs on OpenAI servers, so the event stream leaves the machine for processing. OpenAI also notes the local memory files are not encrypted and other programs running as your macOS user may be able to read them. screenpipe runs capture, indexing, and local search on device in a local SQLite database. Optional cloud AI, sync, connectors, and team workflows have separate data paths that users and administrators configure. Local-first should describe the architecture and its boundaries, not imply that every configuration is local-only.
OpenAI did the right thing on consent: Business and Enterprise admins must grant access before any member can enable Computer History, and each member still opts in. Its documentation does not describe a shared workflow layer, customer-owned raw-history storage, or Windows and Linux support. screenpipe adds admin-managed policy, per-device controls, and an option to upload directly to storage the customer owns. That gives security teams a different deployment model when endpoint-local or customer-controlled history is a requirement.
Credit where it is due. Computer History is off by default, it deliberately skips screenshots, screen recordings, microphone input, and system audio, it excludes private browsing, and it gives you deletion by timeframe down to the last ten minutes. If your only requirement is a smarter ChatGPT on a company Mac and you would rather no screen or audio ever be captured, that narrower surface is a feature, not a gap. screenpipe covers more of the work, and it carries the responsibility that comes with that: local-first capture, source you can inspect, and controls for excluding apps, windows, URLs, and time ranges.
FAQ
Disclosure: this comparison is written and maintained by Screenpipe, not an independent review publication.
Computer History is an opt-in feature in the ChatGPT desktop app for macOS. It records interaction events that macOS accessibility exposes, such as clicks, typing, keyboard shortcuts, and app switches. OpenAI processes the temporary event files on its servers to generate memory files stored locally for ChatGPT and Codex. screenpipe builds computer history as a vendor-neutral layer: rich local history that approved agents can query through MCP or API, with source available for inspection. The overlap depends on the job you are buying for: Screenpipe focuses on continuous, searchable screen and audio context, while ChatGPT Computer History may be a better fit for the narrower workflows described above.
ChatGPT Computer History is a credible choice for teams that value no screenshots, screen recordings, microphone input, or system audio, which is a genuinely smaller capture surface, off by default, with admin approval required before members can opt in on business and enterprise, memories land as plain text files on the mac that you can read, review, or delete. Those strengths should be weighed against the deployment, data-control, platform, and extensibility differences in the table.
Screenpipe is designed for continuous screen and audio capture, local-only capture and search, cross-platform deployment, and programmatic access through its local API and MCP integrations. Those advantages matter most when privacy, broad work context, or custom automation is the buying criterion.
No. Screenpipe publishes this page. We include ChatGPT Computer History's strengths, avoid a numeric winner score, and state the criteria so readers can verify the claims that matter to them. Product capabilities change, so confirm critical details with each vendor before purchasing.
Evaluate with your own data
Install it, test the workflows that matter, and compare the result against your real requirements—not a vendor scorecard.
