Persistent memory graph for AI agents. Facts, decisions, entities, and relationships that survive across sessions, tools, and providers. MCP server — works with Claude, Cursor, ChatGPT, and any MCP client.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"mie": {
"args": [
"--mcp"
],
"command": "mie"
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
You explained your entire architecture to Claude. Two hours of context, decisions, tradeoffs. Next day, new conversation — it knows nothing. So you explain it again. Then you switch to Cursor for implementation. Zero context. You open ChatGPT to brainstorm a different angle. Blank slate.
This server supports HTTP transport. Be the first to test it — help the community know if it works.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
Click any tool to inspect its schema.
Be the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in productivity / ai-ml
Workspace template + MCP server for Claude Code, Codex CLI, Cursor & Windsurf. Multi-agent knowledge engine (ag-refresh / ag-ask) that turns any codebase into a queryable AI assistant.
Persistent memory using a knowledge graph
Dynamic problem-solving through sequential thought chains
mini cli search engine for your docs, knowledge bases, meeting notes, whatever. Tracking current sota approaches while being all local
MCP Security Weekly
Get CVE alerts and security updates for Mie and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
Stop re-explaining yourself to every AI agent. MIE gives all your agents — Claude, ChatGPT, Cursor, Gemini — a shared, persistent knowledge graph they can read and write. Decisions, context, facts, and relationships survive across sessions, tools, and providers.
You explained your entire architecture to Claude. Two hours of context, decisions, tradeoffs. Next day, new conversation — it knows nothing. So you explain it again. Then you switch to Cursor for implementation. Zero context. You open ChatGPT to brainstorm a different angle. Blank slate.
Every AI agent you use is brilliant but amnesiac. And none of them talk to each other.
MIE fixes this. One knowledge graph. Every agent reads from it. Every agent writes to it. Your decisions, your context, your rules — always available, everywhere.
You: "We chose PostgreSQL over DynamoDB because we need ACID
transactions for the payments module. Alternative was Aurora
but too expensive at current stage."
Claude stores this via MIE
↓
┌─────────────────────────────────────────────┐
│ MIE Knowledge Graph │
│ │
│ Decision: PostgreSQL over DynamoDB │
│ Rationale: ACID transactions for payments │
│ Alternatives: [DynamoDB, Aurora] │
│ Entities: payments-module, PostgreSQL │
│ Status: active │
└─────────────────────────────────────────────┘
↓
Next week, in Cursor, different project:
"What database did we choose and why?"
→ Cursor queries MIE, gets full context instantly
No copy-pasting. No "as I mentioned before." No starting from zero.
| Platform Memory | MIE | |
|---|---|---|
| Cross-agent | ❌ Claude doesn't know what you told ChatGPT | ✅ All agents share the same graph |
| Structured | ❌ Flat text summaries | ✅ Typed nodes: facts, decisions, entities, events |
| Queryable | ❌ Basic keyword recall | ✅ Semantic search, graph traversal, conflict detection |
| Portable | ❌ Locked to one provider | ✅ Your data, your machine, exportable |
| Relationships | ❌ None | ✅ "This decision relates to this entity and was triggered by this event" |
| History | ❌ Overwrites silently | ✅ Invalidation chains — see what changed and why |
brew tap kraklabs/mie
brew install mie
mie init # Quick setup with defaults
mie init --interview # Interactive — asks about your stack, team, and project
Claude Code (.mcp.json):
{
"mcpServers": {
"mie": {
"command": "mie",
"args": ["--mcp"]
}
}
}
Cursor (.cursor/mcp.json):
{
"mcpServers": {
"mie": {
"command": "mie",
"args": ["--mcp"]
}
}
}
That's it. Your agents now share a brain.
MIE isn't a chat log. It stores structured knowledge as a graph:
Facts — Things that are true about your world. "Our API uses JWT with RS256 signing." · "The team is 6 engineers across 3 timezones."
Decisions — Choices with rationale and alternatives. *"Chose Go over Rust for CIE because of CGO CozoDB bindings. Alternativ