Best for
- Agent applications requiring cross-session memory
- Users who prioritize data privacy and prefer local memory storage
L
Lumera Agent Memory
Community
Durable agent memory with Cascade object storage and local FTS index
GitHub source repository ↗
24FMRS · D
This server provides persistent memory for agents, featuring client-side encryption and local full-text indexing, suitable for privacy-conscious and cross-session memory scenarios.
Lumera Agent Memory is an MCP server providing persistent memory for AI agents. It uses Cascade object storage and a local full-text search (FTS) index, supporting cross-session context saving and retrieval with client-side encryption. The server communicates via stdio and is distributed as a Python package.
Tools
The tool list has not been reviewed yet.
Setup
Install the Python package 'lumera-agent-memory' version 1.0.0 via pip. After installation, configure the MCP server in Claude Code to point to the package executable.
Fit and risk
Not for
- Applications needing complex relational queries
- Scenarios requiring large-scale distributed storage
Required permissions
- Access local filesystem to store and retrieve memory data
- May access Cascade object storage service (specific permissions depend on deployment config)
Risks and side effects
- Memory data may contain sensitive information; client-side encryption helps mitigate leaks
- Local index dependency; storage capacity may impact performance
Troubleshooting
- Check that 'lumera-agent-memory' is correctly installed in the Python environment
- Ensure the MCP server configuration command path points to the correct executable
- Verify object storage connection settings (if using remote storage)
Use cases
Provide persistent memory for Claude Code across sessions
Save and retrieve agent context
Search historical memory using local full-text index
Supported clients
ClaudeFull support