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.
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.
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Delete outdated or incorrect memories | forget("memory_abc123") |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
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