In-depth architectural comparison of the Memory and Plur 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
Plur
Knowledge & Memory · Local stdio
Quality: 63/100 (Good) | Auth: No auth required
Verdict Summary: Choose Memory if you need specialized Knowledge & Memory tools running via a local process. Choose Plur 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).
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, Plur belongs to Knowledge & Memory using local stdio subprocess. Select Memory when you need capabilities focused on knowledge & memory and Plur 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.
Plur Tools (15)
plur_learn
Store a correction, preference, or convention
plur_learn_batch
Store many engrams in one call (batch dedup + per-item failure isolation)
plur_recall
Retrieve relevant memories — hybrid (BM25 + embeddings) by default; `mode:"keyword"` for BM25-only
plur_inject_hybrid
Select engrams for current task within token budget
plur_feedback
Rate relevance (trains quality over time)
plur_forget
Retire a memory (activation decays, eventually pruned)
plur_rescope
Move an existing engram to another scope — personal → team, or back
plur_session_scope
Change the session's default write scope mid-session
plur_capture
Record an event — incident, resolution, session milestone
plur_timeline
Query episode history by time, agent, or channel
plur_ingest
Extract engrams from text automatically
plur_sync
Sync via git. `personal` remotes mirror everything (use a private repo); `shared` remotes receive only shared-scope, non-private engrams