Pieces captures your on-screen activity into a personal, on-device long-term memory. Contextium is a shared, curated context layer for your whole team. One remembers what you did; the other briefs every tool and teammate on what the team knows.
Contextium vs Pieces, side by side
| Feature | Contextium | Pieces |
|---|---|---|
Team-shared context | One shared workspace | Personal memory |
Works across your AI tools | Any MCP tool | Pieces apps + MCP |
Automatic activity capture | Deliberate, curated | OS-level, rolling window |
Curated, reviewable knowledge | Libraries you edit | Captured, not authored |
Projects, phases & tasks for AI | Built-in | Memory only |
Versioning & audit trail | Built-in + event log | Rolling capture window |
On-device / offline by default | Cloud + desktop app | Local-first design |
Starting price | Free for individuals | Free; Pro ~$19/mo |
Contextium is built for the moment context stops being personal: your teammate’s AI needs the same architecture, conventions and decisions yours has. Update once and every teammate’s tools reflect it.
Pieces’ long-term memory is deliberately personal — it captures what you saw and did on your machine so you can ask “what was I working on yesterday?”. It is not designed to be a team’s shared source of truth.
Contextium holds what your team chose to write down — so the AI’s ground truth is reviewable, current and free of noise. You know exactly what every tool will read.
Pieces captures at the OS level over a rolling window (around nine months). That breadth is the point — but captured context includes everything on screen, and what the AI recalls is selected from activity, not curated by the team.
Contextium also carries live project state — workflows, phases, tasks — so any connected tool knows where the team left off and what is next, not just what happened.
Pieces answers time-based questions about your past activity well. Forward-looking, team-level state — who is doing what, which phase is next — is outside its model.
The reasons to choose Contextium hold no matter what you're switching from.
Works with any MCP-compatible AI tool — Claude, Cursor, Copilot, Gemini and more. Your context is never trapped in one editor or model.
Relevance-based loading serves the context each task needs — not your whole knowledge base on every request.
Every change is versioned with an event log, so teams can see who changed what and roll back.
Free for individuals, one simple per-seat price for teams. No usage meters or surprise overage bills.
They answer different questions — many devs run both
Pieces stays useful for “what was I doing?” questions about your own activity. Nothing to migrate away.
Architecture, conventions, decisions and project state go into a shared workspace your whole team can read and edit.
Add the Contextium MCP URL to Claude, Cursor, Copilot and the rest. Every teammate’s tools now load the same curated context.
They overlap less than they appear to. Pieces is personal, automatic memory of your own activity; Contextium is shared, curated context for a team. If your problem is “my teammate’s AI doesn’t know what mine knows”, that is Contextium’s job, not Pieces’.
No. Contextium only holds what you and your team deliberately put in it. That makes its contents reviewable and auditable — and means nothing is captured without your intent.
Yes, and some developers do: Pieces for personal recall on your machine, Contextium as the team’s shared source of truth across tools. They connect to your AI tools independently.
Different models: Pieces is local-first with on-device storage by default, which is genuinely strong for personal privacy. Contextium is a hosted workspace where every change is versioned with an event log — built for teams that need shared access with governance.
Give the whole team one shared context across every AI tool. Free for individuals.
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