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  3. Naumu
  4. vs MCP Memory Server
Side-by-Side Model Context Protocol Comparison

Naumu vs MCP Memory Server

In-depth architectural comparison of the Naumu and MCP Memory Server 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

Naumu
Knowledge & Memory · Local stdio
Quality: 55/100 (Good) | Auth: No auth required
MCP Memory Server
Knowledge & Memory · Local stdio
Quality: 63/100 (Good) | Auth: API Key required
Verdict Summary: Choose Naumu if you need specialized Knowledge & Memory tools running via a local process. Choose MCP Memory Server 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?

Naumu logo

Choose Naumu 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).
  • You have access to required keys: NAUMU_API_KEY, NAUMU_API_URL.
  • Primary tools included: naumu_list_graphs, naumu_create_graph, naumu_list_members.
Explore Naumu Details
MCP Memory Server logo

Choose MCP Memory Server when:

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer local stdio subprocess transport architecture.
  • Your security boundary fits: API Key required (Freemium).
  • You have access to required keys: MNEMOVERSE_API_KEY, MNEMOVERSE_API_URL.
  • Primary tools included: memory_write, memory_read, memory_list_recent.

Feature & Specification Comparison

Specification
Naumu logo
Naumu
Knowledge & Memory
MCP Memory Server logo
MCP Memory Server
mnemoverse
Knowledge & Memory
SummarySearch, extend, and act on your team's Naumu knowledge graph: notes, threads, and nodes.Hosted memory that learns and forgets — feedback re-ranks what helps, recall fades by recency, similar memories consolidate. One key across Claude, Cursor, VS Code & ChatGPT.
Category & ScopeKnowledge & Memory

Tools & Capabilities Breakdown

Naumu Tools (52)

naumu_list_graphs
List every space (graph) the key can access, with ids, names, and roles
naumu_create_graph
Create a new, empty space owned by the authenticated user
naumu_list_members
List a space's members with their roles
naumu_whoami
Return who the calling key is (user, or bot identity with its graph and allowed tools)
naumu_get_schema
Get a space's schema (node types, attributes, connections)
naumu_update_schema
Replace the schema with a full new definition

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).

Naumu Configuration
mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "naumu": {
      "command": "npx",
      "args": [
        "-y",
        "-p",
        "@naumu/mcp",
        "naumu-mcp"
      ],
      "env": {
        "NAUMU_API_KEY": "YOUR_NAUMU_API_KEY_HERE",
        "NAUMU_API_URL": "YOUR_NAUMU_API_URL_HERE"
      }
    }
  }
}
MCP Memory Server Configuration
mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "mnemoverse-mcp-memory-server": {
      "command": "npx",
      "args": [
        "-y",
        "@mnemoverse/mcp-memory-server@latest"
      ],
      "env": {
        "MNEMOVERSE_API_KEY": "YOUR_MNEMOVERSE_API_KEY_HERE",
        "MNEMOVERSE_API_URL": "YOUR_MNEMOVERSE_API_URL_HERE"
      }
    }
  }
}

Frequently Asked Questions

Naumu is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, MCP Memory Server belongs to Knowledge & Memory using local stdio subprocess. Select Naumu when you need capabilities focused on knowledge & memory and MCP Memory Server when you require tools for knowledge & memory.

More alternatives to NaumuMore alternatives to MCP Memory ServerKnowledge & Memory category hubCanonical compare URL

Related MCP Server Comparisons

Popular comparisons with Naumu

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Popular comparisons with MCP Memory Server

  • Moxie Docs MCP logo
Explore MCP Memory Server Details
Knowledge & Memory
Quality signal55/100 (Good)63/100 (Good)
Transport ProtocolLocal Subprocess (stdio)Local Subprocess (stdio)
Auth RequirementNo auth requiredAPI Key required
Pricing ModelFree / Open SourceFreemium
Required Env Vars
NAUMU_API_KEYNAUMU_API_URL
MNEMOVERSE_API_KEYMNEMOVERSE_API_URL
Compatible Clients
Claude DesktopCursorWindsurfClineVS Code
Claude DesktopCursorWindsurfClineVS Code
Install path signalnpx · highnpx · high
Engagement & Health 0 views 0 copies 0 upvotes 0 stars 2 views 0 copies 0 upvotes 26 stars
Verified / OfficialCommunity ListingCommunity Listing
Open full listingView Naumu ListingView MCP Memory Server Listing
naumu_add_node_type
Add one node type without resending the whole schema
naumu_add_connection
Add one connection from an existing node type to another
naumu_add_attribute
Add or extend an attribute on an existing node type
naumu_list_schema_violations
Audit a space against its schema and report violations
naumu_search
Hybrid (meaning plus text) search over graph nodes
naumu_filter
Filter nodes by type and attributes, with deterministic and complete results
+40 more tools listed on main page

MCP Memory Server Tools (11)

memory_write
Store a long-term memory that persists across sessions and across every AI tool the user has connected to Mnemoverse (Claude, ChatGPT, Cursor, VS Code). Suited to durable information: a stated preference, a decision, a fact about people, roles or project setup, a lesson learned; transient chatter that only matters this turn does not belong here. Never store passwords, API keys, payment data, MFA codes, government IDs, or health records. Behavior: an importance gate may filter low-value writes, so the result tells you whether the memory was stored or filtered. Write `content` as a self-contained statement that still makes sense when recalled out of context.
memory_read
Search long-term memory for user preferences, past decisions, project setup, people, or earlier context. The memory persists across sessions and across every AI tool the user has connected (Claude, ChatGPT, Cursor, VS Code). It applies when an answer may depend on something from an earlier session or another tool; it is not needed for general world knowledge. Returns matches ranked by relevance (or newest-first with order_by: 'recency'); each result carries an id; after the answer, memory_feedback takes these ids to record which memories helped. A wrong or stale memory is corrected by writing a fresh one with memory_write, not by deleting it.
memory_list_recent
List the NEWEST memories first — no search query needed. Semantic search answers 'what do I know about X'; this answers 'what happened lately': resuming work after a break, catching up on a shared room ('any new messages?'), or reviewing what was saved recently. Pass `since` (your last-seen time) to get only what's new, and page through older entries with the returned cursor. Complete by construction WITHIN ONE SCOPE — nothing is skipped there, unlike a semantic search. A page is also bounded by SIZE, so a page of long entries comes back shorter than `limit` and hands you a cursor for the rest — nothing is dropped, and following the cursor is how you get it. To catch up on a shared room you MUST pass its address as `domain`: rooms are separate stores and an unscoped call never covers them.
memory_feedback
Report whether memories returned by memory_read were actually helpful. This is a learning signal, not a log: positive feedback raises a memory's ranking so it surfaces faster next time (across all of the user's tools), negative feedback lowers it so other memories out-rank it — nothing is erased and nothing decays with time. Use it after an answer that relied on or rejected memories from memory_read: pass the ids of those memories as memory_ids, with outcome 1 when they helped and -1 when they were wrong or stale. For memories read from a shared room, also pass that room's address as domain; your own memories need no domain. A read-only room member cannot rate the room's memories.
memory_stats
Get an overview of the stored memory: total count, the number of learned concept associations, the list of domains, and average quality scores. This memory is shared across all AI tools the user has connected to Mnemoverse. Use it to orient yourself, to confirm the exact domain name before writing to it, or when the user asks what you remember. Read-only — changes nothing.
memory_create_room
Create a SHARED memory room — a space OTHER people's assistants can read, and write too when their invite granted read_write (the default scope), across Claude/ChatGPT/Cursor. Use when the user wants to share context or collaborate with someone else (e.g. 'make a room for me and my teammate'). Returns the room's address; pass that address as the `domain` on memory_write/memory_read to use it, and on memory_list_recent to catch up on what others added. People join through an invite minted with memory_invite_to_room.
memory_invite_to_room
Mint an invite for a room you own and get a ready-to-forward message. An invite is single-use by default; pass max_uses to let several people join with the same one. The user sends that message to the person they want to add (any messenger); the recipient opens the link or tells THEIR assistant the code to join. Use when the user asks to invite someone to a room they own, including one just created with memory_create_room.
memory_join_room
Join a shared memory room using an invite code (starts with 'mnvr_'). Use when the user pastes an invite code or says something like 'join room with code ...'. The result gives the room's address, which is the `domain` for reading the shared room with memory_read, and tells you what you may do with it: memory_write to that address is only allowed when your membership scope is read_write; a read-only membership has that write refused; and when the server does not report a scope, whether memory_write would succeed is stated as unknown rather than promised either way.
memory_list_rooms
List the shared memory rooms you can use — the ones you OWN plus the ones you've JOINED — each with the address to pass as `domain` on memory_read, and on memory_write too where your membership scope is read_write; a read-only membership has that write refused. Use this to RE-FIND a room in a new session (e.g. 'what rooms do I have?', 'resume the room with my teammate') instead of having to create or re-join it.
vault_list
List the secrets stored in your Mnemoverse Vault — by ALIAS and purpose only; the secret VALUE is never returned or shown to you, and no tool on this server returns it. Use this to check WHICH secrets the user has stored and under what alias (e.g. the user says 'do I have a GitHub token saved?'). Only YOUR account's secrets are listed.
memory_graph
Reads the association edges around given concepts: which concepts the memory has linked together, with each link's weight, outcome valence and co-activation count. Use to inspect what a memory store has learned or to explain why a read expanded to a concept. Reads your own graph, or a shared room's when its address is passed as domain; any other domain value has no effect. At depth 2 or 3 the engine drops edges below weight 0.05 unless min_weight is set. Read-only.
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