Mnemo MCP vs Memory Os Cli — MCP Server Comparison | AllMCPs
Side-by-Side Model Context Protocol Comparison
Mnemo MCP vs Memory Os Cli
In-depth architectural comparison of the Mnemo MCP and Memory Os Cli 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
Mnemo MCP
Knowledge & Memory · Local stdio
Quality: 64/100 (Good) | Auth: No auth required
Memory Os Cli
Knowledge & Memory · Local stdio
Quality: 65/100 (Great) | Auth: other
Verdict Summary: Choose Mnemo MCP if you need specialized Knowledge & Memory tools running via a local process. Choose Memory Os Cli 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 Mnemo 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).
Store NEW information. Use for preferences, decisions, facts.
ACTION GUIDE — when to use:
- Use when saving new information for the first time.
Example: content='User prefers dark mode', category='preference', tags=['ui']
search_memory
Find existing memories by natural language query. Always search before adding.
ACTION GUIDE — when to use:
- Use BEFORE adding new information to avoid duplicates.
Example: query='dark mode preference'
list_memories
Browse all memories, optionally filtered by category.
ACTION GUIDE — when to use:
- Use when you want to view a broad set of memories, or see what's in a specific category.
Example: category='preference', limit=10
update_memory
Modify an EXISTING memory by ID. Get memory_id from search results.
ACTION GUIDE — when to use:
- Use when an existing fact or preference changes.
Example: memory_id='abc123', content='User now prefers light mode'
delete_memory
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).
Mnemo MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Memory Os Cli belongs to Knowledge & Memory using local stdio subprocess. Select Mnemo MCP when you need capabilities focused on knowledge & memory and Memory Os Cli when you require tools for knowledge & memory.
Remove a memory by ID.
ACTION GUIDE — when to use:
- Use when a memory is completely outdated, incorrect, or explicitly requested to be forgotten.
Example: memory_id='abc123'
export_memories
Export all memories as JSONL.
ACTION GUIDE — when to use:
- Use when the user requests a backup or raw dump of their memory database.
import_memories
Import memories from JSONL data or a list of objects.
ACTION GUIDE — when to use:
- Use when restoring from a backup or migrating data into the memory system.
Example: data='[{"content": "example"}]', mode='merge'
memory_stats
Show database statistics (total memories, categories, embedding status).
ACTION GUIDE — when to use:
- Use when you need to understand the scale or health of the memory database, or check if embeddings are enabled.
restore_memory
Restore an archived memory by ID.
ACTION GUIDE — when to use:
- Use to bring a previously archived memory back into the active search pool.
Example: memory_id='abc123'
archived_memories
List archived memories.
ACTION GUIDE — when to use:
- Use to view memories that have been soft-deleted or automatically archived due to low importance/recency.
consolidate_memories
Summarize similar memories in a category (requires LLM API keys).
ACTION GUIDE — when to use:
- Use when a category has too many redundant or closely related memories and needs cleanup.
Example: category='preference'
memory
[DEPRECATED — use the granular tools (add_memory, search_memory, ...) instead; this composite tool will be removed in a future release]
Legacy dispatcher for backward compatibility. Use specialized tools (add_memory, search_memory, etc.) instead.
Persistent memory store. Actions: add|search|list|update|delete|export|import|stats|restore|archived|consolidate.
ACTION GUIDE — when to use each:
- add: Store NEW information. Requires 'content'. Use when saving preferences, decisions, facts for the first time.
Example: action='add', content='User prefers dark mode', category='preference', tags=['ui']
- search: Find existing memories by natural language query. Requires 'query'. Use BEFORE add to avoid duplicates.
Example: action='search', query='dark mode preference'
- update: Modify an EXISTING memory by ID. Requires 'memory_id' (from search/list results). Use when a fact changes.
Example: action='update', memory_id='abc123', content='User now prefers light mode'
- list: Browse all memories, optionally filtered by category. No query needed.
- delete: Remove a memory by ID. Requires 'memory_id'.
- stats: Show database statistics (total memories, categories, embedding status).
- export: Export all memories to JSONL format.
- import: Import memories from JSONL data. Requires 'data'.
- archived: List archived memories. Optionally filter by limit.
- restore: Restore an archived memory by ID. Requires 'memory_id'.
- consolidate: Summarize and consolidate similar memories in a category using LLM. Requires 'category'.
WORKFLOW: search -> not found? -> add. Found outdated? -> update (with memory_id from results).
PROACTIVE: save user preferences, decisions, corrections, project conventions.
+3 more tools listed on main page
Memory Os Cli Tools (20)
get_mcp_identity
Check XMemo connection status and the connected account/agent.
remember
Save a memory so it can be recalled in future conversations.
recall
Recall the most relevant saved memories before answering.
recall_context
Read a multi-memory context pack. Requires memory:read and does not change content. Use when many memories need explicit budgets; use recall for lightweight answer or get_project_context for project snapshot. max_items/max_tokens bound rendered output.
memory_stats
Show aggregate statistics for XMemo memories.
update_memory
Update the content or metadata of an existing memory.
explain_memory
Explain why a memory exists or matched a query.
restore_memory
Restore a previously deleted memory.
add_expense
Create one XMemo Ledger transaction and backing memory. Requires memory:write; it records a new transaction or reuses a semantic duplicate, and never deletes Ledger records. Use it for a purchase, income, refund, or transfer; use list_ledger_transactions or get_monthly_ledger_summary for reads. amount must be positive; transaction_type defaults to expense; blank transaction_date uses today's UTC date.
Persistent AI memory with SQLite hybrid search (FTS5 + semantic). Built-in Qwen3 embedding, rclone sync across machines. Zero config, no cloud, no limits.
XMemo is user-owned memory for AI agents over a hosted Streamable HTTP MCP endpoint. Save, search, recall, and manage scoped memories across Copilot, Claude, ChatGPT, IDEs, and CLIs. https://xmemo.dev/mcp