A side-by-side look at the Cognitive AI Memory and Memorix MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Cognitive AI Memory for knowledge & memory work as a local process; choose Memorix for knowledge & memory as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Cognitive AI Memory when
You need dedicated capabilities in the Knowledge & Memory domain.
No tool names declared yet. Check the project README from the listing page.
Memorix 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 is categorized under Knowledge & Memory and uses a local stdio subprocess. Memorix belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Cognitive AI Memory for knowledge & memory work and Memorix 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.
Cognitive AI Memory has no declared pricing — check the project's own site. Memorix is listed as free. Auth: no auth required. 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 memorix 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. Memorix has 53/100 (Good) with 2 views, 0 installs and 848 GitHub stars.