mie

MIE (Memory Intelligence Engine) is a local/persistent memory layer for AI agents. It exposes an MCP server with tools to store, query, update, delete, export, and repair a typed knowledge graph (facts/decisions/entities/events/topics) backed by an embedded graph database (CozoDB) and optional local embeddings (e.g., via Ollama).

Evaluated Mar 30, 2026 (21d ago)
Homepage ↗ Repo ↗ Ai Ml ai-agents ai-memory mcp knowledge-graph graph-database semantic-search embeddings local-first go
⚙ Agent Friendliness
52
/ 100
Can an agent use this?
🔒 Security
25
/ 100
Is it safe for agents?
⚡ Reliability
29
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
78
Documentation
72
Error Messages
0
Auth Simplicity
25
Rate Limits
20

🔒 Security

TLS Enforcement
20
Auth Strength
10
Scope Granularity
30
Dep. Hygiene
45
Secret Handling
30

Security controls are not detailed in the provided README. The system appears local-first and uses MCP over stdio (likely Unix domain socket/daemon), but no authentication/authorization, encryption-in-transit requirements, or secrets-handling practices are documented. Embeddings provider may involve local services (Ollama) and optional embedding configuration; ensure embedding inputs/outputs and logs are handled safely. AGPL licensing suggests open-source code availability, but dependency/Vulnerability posture is not verifiable from provided content.

⚡ Reliability

Uptime/SLA
0
Version Stability
45
Breaking Changes
40
Error Recovery
30
AF Security Reliability

Best When

You run AI agents on your machine (or controlled environment) and want a persistent, queryable, structured memory graph that multiple MCP-capable clients can share.

Avoid When

You need fine-grained user/session authorization across untrusted users/agents, or you require published uptime/SLAs and cloud-grade reliability guarantees.

Use Cases

  • Cross-session, cross-agent sharing of structured “memory” (decisions, facts, entities, events).
  • Building agent workflows that retrieve relevant context via semantic/graph queries before answering.
  • Importing project knowledge (e.g., ADRs/markdown/git history) into a persistent memory graph.
  • Detecting contradictions/conflicts in stored knowledge and invalidating outdated items with history preserved.
  • Exporting/importing knowledge graphs for portability and backup/restore.

Not For

  • High-security multi-tenant SaaS memory without strong access controls (no cloud auth model described).
  • Use cases that require a managed hosted service with guaranteed uptime/SLA.
  • APIs where you need a REST/GraphQL/SDK-first developer experience (MCP/CLI-first).

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: None described for local MCP/CLI usage (no auth section in provided content). Optional tool whitelisting/blacklisting via config include_tools/exclude_tools (access control not the same as auth).
OAuth: No Scopes: No

No authentication/authorization model is described in the provided README. Access appears intended for local/control-plane usage where agents are trusted.

Pricing

Free tier: No
Requires CC: No

AGPL-3.0 open-source licensing with optional commercial license mentioned; README does not describe hosted pricing or usage-based billing.

Agent Metadata

Pagination
mentioned (mie_list includes pagination)
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • No explicit auth; ensure only trusted MCP clients can reach the server/tools.
  • Tool behavior and idempotency semantics are not specified in the README; agents should treat write operations as potentially stateful unless confirmed by docs/tests.
  • Embeddings are optional; semantic queries may behave differently depending on embedding availability and provider configuration.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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