Codebase Memory MCP vs Memory — MCP Server Comparison | AllMCPs
Side-by-Side Model Context Protocol Comparison
Codebase Memory MCP vs Memory
In-depth architectural comparison of the Codebase Memory MCP and Memory 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
Codebase Memory MCP
Knowledge & Memory · Local stdio
Quality: 72/100 (Great) | Auth: No auth required
Memory
Knowledge & Memory · Local stdio
Quality: 55/100 (Good) | Auth: No auth required
Verdict Summary: Choose Codebase Memory MCP if you need specialized Knowledge & Memory tools running via a local process. Choose Memory 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?
Choose Codebase Memory MCP 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).
Code-intelligence engine that indexes a repo into a persistent knowledge graph — functions, classes, call chains, HTTP routes, cross-service links. 159 languages via tree-sitter + Hybrid LSP, sub-ms structural queries, 99% fewer tokens than grep. Single static binary, zero dependencies, 100% local. npx codebase-memory-mcp
Index a repository into the graph. Auto-sync keeps it fresh after that.
list_projects
List all indexed projects with node/edge counts.
delete_project
Remove a project and all its graph data.
index_status
Check indexing status of a project.
search_graph
Structural, BM25, and semantic search. Page structural rows with `offset`/`limit` and ranked semantic rows independently with `semantic_offset`/`semantic_limit`.
trace_path
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).
Codebase Memory MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Memory belongs to Knowledge & Memory using local stdio subprocess. Select Codebase Memory MCP when you need capabilities focused on knowledge & memory and Memory when you require tools for knowledge & memory.
Grep-like text search within indexed project files.
+2 more tools listed on main page
Memory Tools (9)
zhiji_workspace_assemble
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.
zhiji_memory_ingest
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.