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

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

Memmy

Freemium

A local-first AI memory layer that lets the desktop app, CLI, and external AI tools share the same long-term context about you.

Self-Evolving Long-Term Memory: Automatically ingests your local AI collaboration history and structures scattered conversations and decisions into evolving memory.
Cross-Tool Memory Relay: Switch between Cursor, Claude, and other agents without re-explaining project context — Memmy carries decisions across tools.
Local-First Architecture: Memory stays on your machine, so preferences and history are not tied to a single vendor's cloud.
Desktop App and CLI Access: Read and write the same memory from the desktop app or the command line, so scripts and agents share one source of truth.
External Agent Integration: Expose the same memory to other AI agents so every tool has consistent knowledge of your preferences and decisions.
Preference and Decision Capture: Records rules like preferred frameworks and stylistic choices so you never need to repeat them in each new session.
Cross-Platform Downloads: Native builds for Mac ARM64 and Windows x64.
Free Trial Tokens: New users get a large token allotment to try Memmy against their real workflow before paying.

Switching Between Cursor and Claude Code: Carry project decisions, style, and open questions across coding assistants without re-briefing.
Personal Assistant Continuity: Keep a consistent long-term memory of your goals and preferences across chat, coding, and writing agents.
Team Onboarding via Shared Memory: Bootstrap a new agent on the same structured memory another agent has been building up.
Local-Only Knowledge Work: Store preferences and history on-device for privacy-sensitive workflows.
CLI-Driven Automation: Use the CLI to seed or query memory from scripts that run alongside interactive AI sessions.
Long Projects: Maintain evolving technical decisions across weeks of work with multiple AI tools without drift.

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.