Memory vs Screenpipe — MCP Server Comparison | AllMCPs
Side-by-Side Model Context Protocol Comparison
Memory vs Screenpipe
In-depth architectural comparison of the Memory and Screenpipe MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Memory
Knowledge & Memory · Local stdio
Quality: 55/100 (Good) | Auth: No auth required
Screenpipe
Knowledge & Memory · Local stdio
Quality: 61/100 (Good) | Auth: No auth required
Verdict Summary: Choose Memory if you need specialized Knowledge & Memory tools running via a local process. Choose Screenpipe if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
M
Choose Memory when:
You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Local-first workflow memory for AI agents. screenpipe lets MCP clients search selected screen, audio, app, and meeting context and turn real work into cited notes, SOPs, workflow reports, and automation candidates.
Flagship.** One call returns everything needed to understand this user for a query — relevant memories + profile + confirmed facts + behavioral inferences (plus counterfactual & cross-domain hints). Drop straight into any LLM's context.
zhiji_memory_search
Lighter, recall-only: the 11-stage hybrid pipeline (trigram FTS + semantic + time-decay), returns scored snippets with sources.
zhiji_profile_get
7-layer / 37-dim user profile as an inject-ready natural-language summary.
zhiji_facts_get
Structured atomic facts (subject attribution, confidence, conflict status) — for exact names/dates/counts, not narrative.
zhiji_prospective_due
Due/upcoming intentions (todos, promises, plans) within a time window — for proactively nudging the user.
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Memory is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Screenpipe belongs to Knowledge & Memory using local stdio subprocess. Select Memory when you need capabilities focused on knowledge & memory and Screenpipe when you require tools for knowledge & memory.
Write a conversation turn to long-term memory; async embedding + profile/fact extraction + importance scoring follow. **Text only.
zhiji_ingest_file
Multimodal ingest — audio / image / PDF / Word / Excel / video → Whisper transcribe / Tesseract OCR / doc parse → memory. Audio & video also get acoustic-emotion analysis.
zhiji_feedback
Thumbs up/down on the last recall/answer → feeds the self-evolution reward and reinforces (or penalizes) the Q-value of recently retrieved memories. The "gets better the more you use it" loop.
zhiji_status
Health & memory scale (files / chunks / FTS availability). Call first to verify connectivity.
Screenpipe Tools (0)
No explicit tool names declared in metadata yet. Check project README on main listing page.