SynapCores MCP Server

Give Claude, Cursor, Windsurf, VS Code, Zed, or any Model Context Protocol client a full AI-native database. SynapCores puts SQL, vector search, a Cypher graph, in-database AutoML, LLM generation and agent memory in one self-hosted engine. This server exposes all of it as MCP tools.

• One server, every data model. Query tables, run semantic search, traverse a graph, and train and score ML models from the same connection.

• No SQL dialect to learn. The tools wrap the engine's AI functions, so an assistant can run semantic search or train a model directly.

• Your data stays with you. SynapCores runs on your machine or your servers. The Community Edition is free.

• Zero dependencies. One small Node.js package (Node 18+).

Try SynapCores in the browser first: synapcores.com/playground

Tools

The tools come from the SynapCores engine itself, so they update when you upgrade the engine.

Related MCP server: NLQueries

1. Run SynapCores

curl -fsSL https://get.synapcores.com | sh

Or use Docker (synapcores/community on Docker Hub). See synapcores.com/download. The gateway listens on http://127.0.0.1:8080 by default.

2. Add the server to your client

Claude Code

claude mcp add synapcores \
  --env SYNAPCORES_URL=http://127.0.0.1:8080 \
  --env SYNAPCORES_TOKEN=your-api-key \
  -- npx -y @synapcores/mcp

Claude Desktop, Cursor, Windsurf, and other JSON-config clients

{
  "mcpServers": {
    "synapcores": {
      "command": "npx",
      "args": ["-y", "@synapcores/mcp"],
      "env": {
        "SYNAPCORES_URL": "http://127.0.0.1:8080",
        "SYNAPCORES_TOKEN": "your-api-key"
      }
    }
  }
}

Config file locations:

• Claude Desktop: claude_desktop_config.json

• Cursor: ~/.cursor/mcp.json

• Windsurf: ~/.codeium/windsurf/mcp_config.json

VS Code

{
  "servers": {
    "synapcores": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@synapcores/mcp"],
      "env": { "SYNAPCORES_URL": "http://127.0.0.1:8080", "SYNAPCORES_TOKEN": "your-api-key" }
    }
  }
}

LangChain, LangGraph, CrewAI

Any MCP adapter works. For example, with langchain-mcp-adapters:

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "synapcores": {
        "command": "npx",
        "args": ["-y", "@synapcores/mcp"],
        "env": {"SYNAPCORES_URL": "http://127.0.0.1:8080", "SYNAPCORES_TOKEN": "your-api-key"},
        "transport": "stdio",
    }
})
tools = await client.get_tools()

Configuration

Every tool call goes through the gateway's authentication and tenant isolation. The assistant sees only what its API key is allowed to see. For read-only exploration, give it a read-only key.

Try it

"What tables are in my SynapCores database, and how many rows does each have?"

"Train a model on customers to predict churned, then show the 10 highest-risk customers."

"Find the five support articles most similar to 'reset my password'."

How it works

MCP client  ⇄  stdio  ⇄  @synapcores/mcp  ⇄  HTTPS (JSON-RPC)  ⇄  SynapCores gateway /v1/mcp

The engine hosts the MCP server. This package connects stdio clients to it.

Links

• Website: https://synapcores.com

• Playground: https://synapcores.com/playground

• Docs: https://docs.synapcores.com/mcp-setup/

• Releases: https://github.com/SynapCores/synapcores-releases

License

MIT