Persistent AI memory with hybrid search, entity resolution, and temporal decay.
Use this profile to copy client config, check auth requirements, review tools and resources, and compare related MCP servers before adding it to an AI client.
uvx remembraAdd this server entry to the mcpServers object in your Claude Desktop config, then restart the app.
{
"mcpServers": {
"io-github-remembra-ai-remembra": {
"command": "uvx",
"args": [
"remembra"
]
}
}
}~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonNo remote HTTP endpoint is advertised. Use the package or stdio setup shown in Install.
Remembra — AI Memory Layer is an MCP server for Persistent AI memory with hybrid search, entity resolution, and temporal decay.. It supports STDIO transport.
Use the generated config in Install. This server runs with uvx remembra; add any required environment variables before starting your client.
Choose the Claude Desktop tab in Install and copy the config for uvx remembra. Add required environment variables before starting Claude Desktop.
Choose the Claude Code tab in Install and copy the config for uvx remembra. Add required environment variables before starting Claude Code.
Choose the Codex tab in Install and copy the config for uvx remembra. Add required environment variables before starting Codex.
Choose the Cursor or VS Code tab in Install and copy the config for uvx remembra. Add required environment variables before starting Cursor or VS Code.
Remembra — AI Memory Layer uses STDIO transport. Use the package or command config in Install.
Remembra — AI Memory Layer inventory is listed when the MCP endpoint exposes tools, resources, or prompts. Some servers require auth first.
Remembra — AI Memory Layer does not advertise a verified auth requirement. If discovery fails, it may still need provider login, an API key, a bearer token, or a session header.
| Package | Registry | Version | Inputs |
|---|---|---|---|
remembrastdio | pypi | 0.8.2 | None advertised |