Local Redis memory MCP for AI apps with hybrid caching and optional Mem0 cloud backup.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
Persistent memory for MCP clients (Claude Desktop, Claude Code, Cursor) that runs entirely on your machine, with no accounts, no API keys, and no cloud service required to start.

That single command starts an MCP server backed by an embedded Redis instance and a local vector index. There is no separate database to install and no signup step.
redis-memory-server downloads and manages a local Redis binary for you. It stores memory content and metadata. If it cannot start, r3 falls back to an in-process store.MEM0_API_KEY is set, r3 also syncs to Mem0's cloud API so memories can follow you across machines. Without a key, nothing leaves your machine.Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):
Add to .cursor/mcp.json in your project (or the global Cursor MCP config):
Restart the client after editing config. In a new conversation:
| Tool | Description |
|---|---|
add_memory | Store content with optional metadata and priority |
search_memory | Query memories using semantic or keyword search |
get_all_memories | List stored memories with pagination |
get_memory | Retrieve a specific memory by ID |
update_memory | Modify existing memory content or metadata |
delete_memory | Remove a memory |
deduplicate_memories | Find and merge duplicate memories |
cache_stats | Report cache hit rate and storage stats |
sync_status | Report Mem0 cloud sync status |
optimize_cache | Run cache maintenance |
import_memories | Bulk import memories |
Enhanced mode (default, INTELLIGENCE_MODE=enhanced) adds:
| Tool | Description |
|---|---|
extract_entities | Extract named entities from text |
get_knowledge_graph | Return the entity/relationship graph |
find_connections | Find entities connected to a given entity |
Environment variables, all optional:
| Variable | Description | Default |
|---|---|---|
REDIS_URL | Use an external Redis instead of the embedded one | embedded server |
MEM0_API_KEY | Enables Mem0 cloud sync | unset (local only) |
MEM0_USER_ID | Namespace for memories | default |
INTELLIGENCE_MODE | enhanced or basic | enhanced |
Example with cloud sync enabled:
| r3 | mem0 (OSS) | zep | |
|---|---|---|---|
| Runs fully local with zero config | yes (embedded Redis + vectra) | requires a Postgres/vector DB you configure | requires a Postgres instance you configure |
| Needs an API key to try it | no | no (self-hosted) / yes (cloud) | yes (cloud), or self-hosted setup |
| Optional cloud sync | yes, via Mem0 | n/a (is the cloud option) | yes |
This table only reflects setup requirements observed in each project's own documentation, not benchmark performance or feature completeness. Verify against current upstream docs before relying on it.
See LAUNCH_AUDIT.md for current limitations, including a native module build failure on some macOS setups.
Full documentation at r3.n3wth.com.
MIT
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