Cognitive AI Memory vs Mnema

A side-by-side look at the Cognitive AI Memory and Mnema MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Cognitive AI Memory logoCognitive AI MemoryKnowledge & Memory · Local subprocess (stdio)Ebbinghaus-based persistent memory for Claude. Memories decay with time, strengthen on recall.44FairAuth: not declaredMnema logoMnemaKnowledge & MemoryLocal-first, formally verified memory for AI agents: consult/learn/related/list over MCP.29EmergingAuth: not declared

Verdict: choose Cognitive AI Memory for knowledge & memory work as a local process; choose Mnema for knowledge & memory. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Cognitive AI Memory logoChoose Cognitive AI Memory when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer a local stdio subprocess transport.
Explore Cognitive AI Memory

Mnema logoChoose Mnema when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You have the keys it needs: MNEMA_DATA_DIR, MNEMA_URL, MNEMA_TOKEN.
Explore Mnema

Feature & specification comparison

Rows where the two servers differ are marked.

SpecCognitive AI Memory logoCognitive AI MemoryMnema logoMnema
CategoryKnowledge & MemoryKnowledge & Memory
Quality signal44/100 · Fair29/100 · Emerging
Install commandConfirmedNot confirmed yet
TransportLocal subprocess (stdio)—
AuthNot declaredNot declared
PricingNot declaredNot declared
Required env varsNone listedMNEMA_DATA_DIRMNEMA_URLMNEMA_TOKEN
Verified ownerCommunity listingCommunity listing
GitHub stars2700
Directory activity 3 views 0 installs 0 upvotes 0 views 0 installs 0 upvotes
ToolsNot listedNot listed

Tools & capabilities

Cognitive AI Memory tools

No tool names declared yet. Check the project README from the listing page.

Mnema tools

No tool names declared yet. Check the project README from the listing page.

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Cognitive AI Memory

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "cognitive-ai-memory": {
      "command": "uvx",
      "args": [
        "yourmemory"
      ]
    }
  }
}

Mnema

No confirmed install command for Mnema yet — follow the setup steps linked from its listing page rather than a guessed package name.

Frequently asked questions

Cognitive AI Memory is categorized under Knowledge & Memory and uses a local stdio subprocess. Mnema belongs to Knowledge & Memory and uses an install path we have not confirmed yet. Pick Cognitive AI Memory for knowledge & memory work and Mnema for knowledge & memory.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Mnema has no confirmed install command yet — follow its own setup instructions.

Cognitive AI Memory has no declared pricing — check the project's own site. Mnema has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add cognitive-ai-memory and mnema as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Cognitive AI Memory has a quality signal of 44/100 (Fair) with 3 views, 0 installs and 270 GitHub stars. Mnema has 29/100 (Emerging) with 0 views, 0 installs and 0 GitHub stars.