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cortex-memory-mcp
Advanced tools
Persistent memory for AI agents. An MCP server that gives any AI agent (Claude, Kiro, Cursor, custom) long-term memory across conversations using semantic search.
Your AI agent forgets everything between conversations. Cortex fixes that. Memories are stored in the cloud, semantically indexed, and instantly retrievable — so your agent can remember preferences, decisions, project context, and anything else that matters.
Tools provided:
| Tool | Description |
|---|---|
save_memory | Store facts, preferences, decisions, or insights |
search_memory | Semantic search — find memories by meaning, not keywords |
update_memory | Revise an existing memory when things change |
delete_memory | Remove outdated or incorrect memories |
Memories are automatically enriched with semantic vectors for intelligent retrieval. Each API key gets its own isolated memory space.
npx cortex-memory-init
This will:
Already have a key? Pass it directly:
npx cortex-memory-init ctx_your_key_here
If you prefer to configure manually, add to your MCP config:
{
"mcpServers": {
"cortex-memory": {
"command": "npx",
"args": ["-y", "cortex-memory-mcp"],
"env": {
"CORTEX_API_KEY": "ctx_your_key_here"
}
}
}
}
That's it. Your agent now has persistent memory.
When your agent encounters important information — a user preference, a technical decision, project context — it saves it to Cortex. On subsequent conversations, the agent searches memory for relevant context and picks up where it left off.
Agent → save_memory("User prefers TypeScript over JavaScript")
...next conversation...
Agent → search_memory("language preferences")
→ "User prefers TypeScript over JavaScript"
| Variable | Required | Description |
|---|---|---|
CORTEX_API_KEY | Yes | Your API key from the dashboard |
CORTEX_API_URL | No | Custom API endpoint (defaults to hosted service) |
MIT
FAQs
MCP server for Cortex memory service — persistent memory for AI agents
We found that cortex-memory-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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