Back to Protocol

The
Manual.

Integrate universal memory into your AI agents using the Model Context Protocol (MCP).

Quickstart

01

Generate a PAT

Go to your Dashboard and create a new Personal Access Token. This acts as the key for your AI.

02

Select Your Client

Choose your AI client from the tabs on the right to get the correct configuration format.

03

Apply Configuration

Paste the snippet into your client's MCP configuration file or project settings.

04

Add PAT to Config

Replace 'YOUR_PAT_HERE' with your actual generated Personal Access Token.

05

Start Remembering

Your AI now has access to your universal memory. Ask it to 'remember' something!

Core Concepts

Hot Layer

Immediate short-term context (48h). Stored in fast-access buffers for instant recall of the most recent events.

Warm Layer

Semantic indexing via vector embeddings. Optimized for fast similarity search across the last 60 days of activity.

Cold Layer

The permanent Knowledge Graph. Crystallized entries that enable deep relational reasoning and long-term facts.

MCP Implementation

Cortex acts as an MCP Server. Your AI client connects via SSE or Standard IO to explicitly access capabilities like memorize and recall.

mcp_config.json
{
  "mcpServers": {
    "cortex-protocol": {
      "url": "https://cortex-server-685740048714.us-central1.run.app/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT_HERE"
      }
    }
  }
}

Auth & Security

Connections to Cortex are secured via Personal Access Tokens (PATs). These tokens bridge the gap between your secure identity and third-party AI agents.

  • Granular ControlCreate unique tokens for each tool (Cursor, ChatGPT) to monitor access logs independently.
  • Instant RevocationCompromised a token? Revoke it instantly from the Dashboard to cut off all access.

Developer Assets

SKILL.md
Coming Soon
Open Source
GitHub Repo