ainative-memory-mcp

Enhanced MCP knowledge graph memory server with cloud persistence and semantic search. Drop-in replacement for @modelcontextprotocol/server-memory.

Why this instead of server-memory?

Feature	server-memory	ainative-memory-mcp
Storage	Local JSONL file	ZeroDB cloud
Persistence	Lost on machine wipe	Survives forever
Cross-device	No	Yes (same API key = same graph)
Semantic search	No (text match only)	Yes (vector similarity)
Setup	Manual file path	Auto-provisions on first run
Sharing	Copy files around	Share API key

Quick Start

Claude Desktop / Claude Code

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "ainative-memory-mcp"],
      "env": {
        "ZERODB_API_KEY": "ak_your_key"
      }
    }
  }
}

No API key? Just omit it — a free ZeroDB instance is auto-provisioned on first run.

Cursor / Windsurf / VS Code

Same config in your .mcp.json:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "ainative-memory-mcp"],
      "env": {
        "ZERODB_API_KEY": "ak_your_key"
      }
    }
  }
}

Get an API Key

npx zerodb-cli init

Or sign up at ainative.studio.

Tools (10)

All 9 original server-memory tools plus semantic search:

Original Tools

Tool	Description
create_entities	Create new entities with name, type, and observations
create_relations	Create directed relations between entities
add_observations	Add observations to existing entities
delete_entities	Delete entities and their cascading relations
delete_observations	Remove specific observations from entities
delete_relations	Delete specific relations
read_graph	Read the entire knowledge graph
search_nodes	Search by text match (name, type, observations)
open_nodes	Fetch specific entities by name with their relations

New Tool

Tool	Description
search_nodes_semantic	Vector similarity search — find entities by meaning, not just exact text

Semantic Search Example

The original search_nodes only finds exact text matches. search_nodes_semantic understands meaning:

search_nodes("ML frameworks")        -> might find nothing
search_nodes_semantic("ML frameworks") -> finds "PyTorch", "TensorFlow", "JAX"

Environment Variables

Variable	Required	Description
ZERODB_API_KEY	No*	ZeroDB API key (auto-provisions if missing)
ZERODB_PROJECT_ID	No	ZeroDB project ID
ZERODB_API_URL	No	API URL (default: https://api.ainative.studio)

*If no credentials are provided, a free instance is automatically provisioned on first run.

Auto-Provisioning

On first run without credentials:

1. A free ZeroDB instance is provisioned automatically
2. Credentials are saved to .mcp.json and .env in your project
3. A claim URL is printed so you can take ownership of the instance
4. Everything works immediately — no signup required

How It Works

Instead of writing to a local memory.jsonl file, this server:

1. Entities are stored as rows in a ZeroDB NoSQL table (kg_entities)
2. Relations are stored in a separate table (kg_relations)
3. Vector embeddings are automatically generated for each entity via ZeroMemory, enabling semantic search
4. All data persists in the cloud and is accessible from any device with the same API key

Migration from server-memory

1. Replace @modelcontextprotocol/server-memory with ainative-memory-mcp in your MCP config
2. Add ZERODB_API_KEY to your env (or let it auto-provision)
3. Re-create your entities (one-time migration — your old JSONL data stays on disk)

License

MIT