Give any AI agent persistent memory backed by a personal knowledge graph. Works with Claude, Cursor, Windsurf, VS Code, and any MCP-compatible tool.
The MIND MCP Server is an open-source Model Context Protocol server that connects any MCP-compatible AI agent to your personal MIND knowledge graph.
Once installed, your AI agent can query your knowledge graph, store memories, manage tasks and goals, track contacts, and check graph health — with full persistence across sessions, devices, and tools. What you teach Claude Code is available in Cursor. What you decide in one session is remembered in the next.
Your AI Agent ←→ MCP Protocol ←→ MIND MCP Server ←→ MIND Knowledge Graph
(Claude, (stdio) (Node.js) (LightRAG + MongoDB)
Cursor,
Windsurf...)
Sign up at m-i-n-d.ai (free tier available — no credit card required), then navigate to Settings → Developer → Create API Key. Your key will start with mind_.
Requires Node.js 18 or higher.
npm install -g @astramindapp/mcp-server
Verify installation:
mind-mcp --version
Add MIND to your tool's MCP configuration. See the platform-specific configs below.
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"mind": {
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
claude mcp add mind -- env MIND_API_KEY=mind_your_key_here mind-mcp
Create or edit .cursor/mcp.json in your project root, or ~/.cursor/mcp.json globally:
{
"mcpServers": {
"mind": {
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
Edit ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"mind": {
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
Add to your .vscode/mcp.json:
{
"servers": {
"mind": {
"type": "stdio",
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
{
mcp: {
servers: {
mind: {
command: "mind-mcp",
env: { MIND_API_KEY: "mind_your_key_here" }
}
}
}
}
{
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here",
"MIND_BASE_URL": "https://m-i-n-d.ai" // optional, defaults to production
}
}
Once connected, your AI agent has access to these 6 tools:
hybrid (default — combines semantic + graph traversal), mix (balanced), graph (entity relationships), vector (semantic similarity)// Example usage
mind_query({
query: "What is my go-to-market strategy for Q3?",
mode: "hybrid"
})
document (long-form structured content), entry (medium — observations, findings), thought (quick ideas). Defaults to entry.["strategy", "competitor", "learning"]"claude-code", "cursor". Defaults to "mcp-agent".mind_remember({
content: "Decided to prioritize SEO over paid ads in Q3. Reason: CAC too high at $180.",
type: "entry",
title: "Q3 Marketing Decision",
tags: ["marketing", "decision", "q3"],
source: "claude-code"
})
soul (identity/mission), user (user profile/preferences), rules (operating constraints), priorities (current goals), recent (latest activity). Defaults to all sections.// Load full context at session start
mind_context({ sections: ["soul", "user", "rules", "priorities", "recent"] })
// Load just priorities and recent activity
mind_context({ sections: ["priorities", "recent"] })
list, create, update, complete, or deleteaction, someday, waiting, completedlow, medium, high, or urgent// Create a task
mind_life({ action: "create", title: "Ship MCP docs page", priority: "high", due_date: "2026-03-22" })
// List active items
mind_life({ action: "list", status: "action" })
list, create, or updatelead, prospect, partner, customer, or personalnew, qualified, proposal, closed, or lostmind_crm({ action: "create", name: "Jane Smith", email: "jane@acme.com", company: "Acme Corp", type: "lead" })
No parameters required. Returns entity count, relationship count, storage status, credits remaining, and tier.
mind_graph() // → { entities: 1240, relationships: 3800, credits: 450/600, tier: "starter" }
// SESSION START — always do this first
1. mind_context() → Load identity, rules, priorities
2. mind_query(task_query) → Get relevant memories for the current task
// DURING SESSION — as needed
3. mind_query(...) → Before making decisions
4. mind_life(...) → Create/update tasks
// SESSION END — always do this last
5. mind_remember(outcomes) → Store what was decided, learned, or completed
| Variable | Required | Default | Description |
|---|---|---|---|
MIND_API_KEY | Yes | — | Your MIND Developer API key. Get one at m-i-n-d.ai → Settings → Developer. Starts with mind_. |
MIND_BASE_URL | No | https://m-i-n-d.ai | MIND API base URL. Override for self-hosted deployments. |
| Capability | MEMORY.md / flat files | MIND MCP |
|---|---|---|
| Size limit | ~20K chars, then truncated | Unlimited knowledge graph |
| Retrieval | Loads everything every turn | Only retrieves relevant memories |
| Structure | Unstructured text | Entities + relationships + embeddings |
| Search | Keyword on small file | Hybrid semantic + graph traversal |
| Cross-tool | Locked to one tool | Shared across all MCP-compatible agents |
| Documents | Manual | Upload PDFs, Word, URLs, text |
| Tasks | Manual text editing | Structured task management via mind_life |
| Contacts | Not supported | Full CRM via mind_crm |
You can also import the server directly in your own Node.js application:
import { createMindMcpServer, MindClient } from "@astramindapp/mcp-server";
const client = new MindClient({
baseUrl: "https://m-i-n-d.ai",
apiKey: process.env.MIND_API_KEY,
});
const server = createMindMcpServer(client);
// Connect to any MCP transport (stdio, SSE, etc.)