Central Intelligence

Central Intelligence

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

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README

Central Intelligence

Agents forget. CI remembers.

Persistent memory for AI agents. Store, recall, and share information across sessions. Works with Claude Code, Cursor, LangChain, CrewAI, and any agent that supports MCP.

npm License: MIT

Central Intelligence MCP server

Quick Start (30 seconds)

# 1. Get an API key
npx central-intelligence-cli signup

# 2. Add to Claude Code
npx central-intelligence-cli init claude

# Done. Your agent now has persistent memory.

The Problem

Every AI agent session starts from zero. Your agent learns your preferences, understands your codebase, figures out your architecture — then the session ends and it forgets everything. Next session? Same questions. Same mistakes. Same context-building from scratch.

Central Intelligence fixes this.

What It Does

Five MCP tools give your agent a long-term memory:

Tool Description Example
remember Store information for later "User prefers TypeScript and deploys to Fly.io"
recall Semantic search across past memories "What does the user prefer?"
context Auto-load relevant memories for the current task "Working on the auth system refactor"
forget Delete outdated or incorrect memories forget("memory_abc123")
share Make memories available to other agents scope: "agent" → "org"

How It Works

Agent (Claude, GPT, etc.)
    ↓ MCP protocol
Central Intelligence MCP Server (local, thin client)
    ↓ HTTPS
Central Intelligence API (hosted)
    ↓
PostgreSQL + vector embeddings (semantic search)

Memories are stored as text with vector embeddings. Recall uses cosine similarity to find semantically relevant memories, not just keyword matches.

Memory Scopes

Scope Visible to Use case
agent Only the agent that stored it Personal context, session continuity
user All agents serving the same user User preferences, cross-tool context
org All agents in the organization Shared knowledge, team decisions

MCP Server Setup

Claude Code

Add to ~/.claude/settings.json under mcpServers:

{
  "central-intelligence": {
    "command": "npx",
    "args": ["-y", "central-intelligence-mcp"],
    "env": {
      "CI_API_KEY": "your-api-key"
    }
  }
}

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "central-intelligence": {
      "command": "npx",
      "args": ["-y", "central-intelligence-mcp"],
      "env": {
        "CI_API_KEY": "your-api-key"
      }
    }
  }
}

Any MCP-Compatible Client

The MCP server is published as central-intelligence-mcp on npm. Point your MCP client to it with the CI_API_KEY environment variable set.

CLI Usage

# Sign up and get an API key
npx central-intelligence-cli signup

# Add to Claude Code / Cursor
npx central-intelligence-cli init claude
npx central-intelligence-cli init cursor

# Store a memory
npx central-intelligence-cli remember "The user prefers dark mode and TypeScript"

# Search memories
npx central-intelligence-cli recall "what are the user's preferences?"

# Delete a memory
npx central-intelligence-cli forget <memory-id>

# Check connection
npx central-intelligence-cli status

Or install globally for shorter commands:

npm install -g central-intelligence-cli
ci-memory signup
ci-memory remember "User prefers TypeScript"
ci-memory recall "language preferences"

REST API

Base URL: https://central-intelligence-api.fly.dev

All endpoints require Authorization: Bearer <api-key> header.

Create API Key

curl -X POST https://central-intelligence-api.fly.dev/keys \
  -H "Content-Type: application/json" \
  -d '{"name": "my-key"}'

POST /memories/remember

{
  "agent_id": "my-agent",
  "content": "User prefers TypeScript over Python",
  "tags": ["preference", "language"],
  "scope": "agent"
}

POST /memories/recall

{
  "agent_id": "my-agent",
  "query": "what programming language does the user prefer?",
  "limit": 5
}

Response:

{
  "memories": [
    {
      "id": "uuid",
      "content": "User prefers TypeScript over Python",
      "relevance_score": 0.434,
      "tags": ["preference", "language"],
      "scope": "agent",
      "created_at": "2026-03-22T21:42:34.590Z"
    }
  ]
}

POST /memories/context

{
  "agent_id": "my-agent",
  "current_context": "Setting up a new web project for the user",
  "max_memories": 5
}

DELETE /memories/:id

POST /memories/:id/share

{
  "target_scope": "org"
}

GET /usage

Returns memory counts, usage events, and active agents for the authenticated API key.

Self-Hosting

# Clone and install
git clone https://github.com/AlekseiMarchenko/central-intelligence.git
cd central-intelligence
npm install

# Set up PostgreSQL
createdb central_intelligence
psql -d central_intelligence -f packages/api/src/db/schema.sql

# Configure
cp .env.example .env
# Edit .env: set DATABASE_URL and OPENAI_API_KEY

# Run
npm run dev:api

Deploy to Fly.io

fly apps create my-ci-api
fly postgres create --name my-ci-db
fly postgres attach my-ci-db
fly secrets set OPENAI_API_KEY=sk-...
fly deploy

Then point the MCP server to your instance:

{
  "env": {
    "CI_API_KEY": "your-key",
    "CI_API_URL": "https://your-app.fly.dev"
  }
}

Architecture

central-intelligence/
├── packages/
│   ├── api/            # Backend API (Hono + PostgreSQL)
│   │   └── src/
│   │       ├── db/           # Schema, migrations, connection
│   │       ├── middleware/   # Auth, rate limiting
│   │       ├── routes/       # API endpoints
│   │       └── services/     # Business logic (memories, embeddings, auth)
│   ├── mcp-server/     # MCP server (npm: central-intelligence-mcp)
│   └── cli/            # CLI tool (npm: central-intelligence-cli)
├── landing/            # Landing page
├── Dockerfile          # API container
├── fly.toml            # Fly.io config
└── README.md

Pricing

Tier Price Memories Agents
Free $0 500 1
Pro $29/mo 50,000 20
Team $99/mo 500,000 Unlimited

Contributing

Contributions welcome. Open an issue or PR.

License

MIT

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