Which integrations are available for this server?

Uses Express.js as the web application framework to handle HTTP requests and provide REST API endpoints for memory operations.

Built on Node.js runtime environment, providing the server infrastructure for the MemoryAPI REST endpoints and MCP server implementation.

Uses OpenAI's text-embedding-3-small model to generate embeddings for memories, enabling semantic search capabilities based on meaning rather than exact keywords.

Employs PostgreSQL as the underlying database system through Supabase for storing memory records and their vector embeddings.

Utilizes Supabase as the database backend with PostgreSQL and pgvector for storing and retrieving vector embeddings of memories, enabling semantic search functionality.

🧠 MemoryAPI

Persistent memory for AI agents and LLMs — REST API + MCP native

License: MIT MCP Compatible

MemoryAPI gives your AI agent a persistent, searchable memory across sessions. Store memories in natural language, retrieve them semantically — no exact keywords needed.

🌐 memoryapi.org | 📡 API: api.memoryapi.org

Features

🧠 Semantic Search — find memories by meaning, not keywords
🔌 MCP Native — plug into Claude, Cursor, Windsurf instantly
⚡ REST API — simple HTTP endpoints, any language
🔑 API Key Auth — secure, namespaced per agent
📊 Usage Tracking — memory count and plan limits
🌍 Always On — hosted at api.memoryapi.org

Quick Start

1. Get an API Key

curl -X POST https://api.memoryapi.org/keys \
  -H "Content-Type: application/json" \
  -d '{"agent_id": "my-agent", "email": "you@example.com"}'

Returns:

{
  "api_key": "mem_xxxxxxxx.yyyyyyyy",
  "message": "Save this key securely — it will not be shown again."
}

2. Store a Memory

curl -X POST https://api.memoryapi.org/memory \
  -H "Content-Type: application/json" \
  -H "x-api-key: mem_xxxxxxxx.yyyyyyyy" \
  -d '{"content": "User prefers dark mode and React Native"}'

3. Search Memories

curl "https://api.memoryapi.org/memory?query=what+does+the+user+prefer" \
  -H "x-api-key: mem_xxxxxxxx.yyyyyyyy"

MCP Integration

Add to your MCP client config (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "memoryapi": {
      "url": "https://api.memoryapi.org/mcp",
      "headers": {
        "x-api-key": "mem_xxxxxxxx.yyyyyyyy"
      }
    }
  }
}

Available MCP Tools

Tool	Description
`store_memory`	Store a memory in natural language
`search_memory`	Semantically search memories
`list_memories`	List all stored memories
`delete_memory`	Delete a memory by ID

REST API Reference

`POST /memory`

Store a memory.

Headers: x-api-key: your-key

Body:

{
  "content": "string (required, max 10,000 chars)",
  "metadata": { "type": "preference" }
}

`GET /memory?query=...`

Semantic search across memories.

Headers: x-api-key: your-key

Query params:

query (required) — natural language search
limit (optional, default 10) — max results
threshold (optional, default 0.4) — similarity threshold

`GET /memory/list`

List all memories for the agent.

Query params:

limit (default 50)
offset (default 0)

`DELETE /memory/:id`

Delete a specific memory.

`POST /keys`

Generate a new API key.