MIE FAQs

Question 1

How does MIE differ from platform-specific AI memories (e.g., ChatGPT, Claude)?

Accepted Answer

MIE offers cross-agent memory, structured knowledge (facts, decisions, entities with relationships), advanced queryability (semantic search, graph traversal), portability (your data, your machine), and historical context through invalidation chains, unlike isolated platform memories.

Question 2

What is MIE and what problem does it solve?

Accepted Answer

MIE (Memory Intelligence Engine) provides a shared, persistent knowledge graph for all your AI agents. It solves the 'amnesiac AI' problem by ensuring agents retain context, facts, and decisions across sessions and tools, eliminating redundant explanations and improving consistency.

Question 3

What types of information can MIE store?

Accepted Answer

MIE stores structured knowledge as a graph, including Facts, Decisions (with rationale and alternatives), Entities (people, projects, technologies), Events (timestamped occurrences), and Topics. These are interconnected through typed relationships for rich context.

Question 4

Does MIE incur additional server-side inference costs?

Accepted Answer

No. MIE utilizes an 'agent-as-evaluator' architecture. The connected AI agent's LLM performs classification and decision-making on what to store, meaning MIE itself incurs zero additional server-side inference costs for memory operations.

Question 5

How do I integrate MIE with my AI agents?

Accepted Answer

MIE integrates via the Model Context Protocol (MCP). After installing and initializing MIE, you configure your AI agent's MCP settings (e.g., in a `.mcp.json` file for Claude or Cursor) to point to the MIE server command, allowing agents to read from and write to the shared graph.

MIE

MIE

Key Features

Use Cases

Key Features

Use Cases