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MCP SERVER

MIE - Memory Intelligence Engine

by kraklabs

One knowledge graph every assistant reads and writes, so a decision explained to Claude is available in Cursor next week.

Agent Memory
Summary
Structured memory, with no second model deciding what matters.

Most memory servers run their own LLM to classify what to keep, which means your memory layer has a bill and an opinion. MIE inverts it: mie_analyze returns the related context and the agent already in the loop makes the call. What you get out of that is a graph rather than a pile of summaries — decisions carry rationale and alternatives, superseded facts are invalidated rather than overwritten, and mie_conflicts will tell you when two things you stored disagree.

What it is

A local memory server that stores typed nodes — facts, decisions, entities, events and topics — and the relationships between them, then serves that graph to any MCP client. It does no inference of its own: the server hands the agent related context and an evaluation guide, and the agent decides what is worth keeping.

What you get
  • mie_analyze — surfaces existing related memory and possible conflicts before anything is written
  • mie_store — writes a fact, decision, entity, event or topic, with relationships and an optional invalidation of the fact it replaces
  • mie_bulk_store — up to 50 nodes with cross-references in one call, for importing from files or git history
  • mie_query — semantic search, exact substring lookup, or graph traversal from a node
  • mie_get and mie_list — one node in full, or a filtered and paginated table
  • mie_update — invalidate an outdated fact or change a status, with the history preserved
  • mie_delete — remove a node with its embedding and edges, or drop a single relationship
  • mie_conflicts — find pairs of stored facts that look similar but disagree
  • mie_export — the whole graph as JSON or Datalog
  • mie_status and mie_repair — graph health and node counts, and a rebuild of the HNSW indexes when semantic search starts erroring
Requirements

Install the binary with brew tap kraklabs/mie and brew install mie, run mie init, and point clients at mie --mcp. Building from source needs Go 1.24 or later. Semantic search is optional and needs Ollama with nomic-embed-text pulled; without it you still get exact-match search and graph traversal. include_tools and exclude_tools in the config restrict which tools a client is offered, and filtered tools are rejected at call time too. Dual-licensed — AGPL-3.0, or a commercial licence for proprietary use.

Setup effort

One command — brew install kraklabs/tap/mie