Mimir

Mimir

Persistent Memory for AI Agents — MCP-Native. Local-First. Zero Dependencies.

Mimir is a single Rust binary that gives AI agents durable memory across sessions.One binary. One file. No Docker. No Postgres. No cloud. Just persistent memorythat works with any MCP host.

One-Line Install

curl -sSf https://raw.githubusercontent.com/Perseus-Computing-LLC/mimir/main/scripts/install.sh | sh

That's it. Mimir is installed to ~/.local/bin/mimir. Start it:

mimir serve --db ~/.mimir/data/mimir.db

Connect any MCP host (Claude Desktop, Cursor, Hermes Agent, Perseus, etc.):

{
  "mcpServers": {
    "mimir": {
      "command": "mimir",
      "args": ["serve", "--db", "~/.mimir/data/mimir.db"]
    }
  }
}

30-Second Quickstart

# Start Mimir
mimir serve --db memory.db &
sleep 1

# Remember a fact (via MCP JSON-RPC on stdio)
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"mimir_remember","arguments":{"category":"demo","key":"hello","body_json":"{\"text\":\"Hello from Mimir!\"}"}}}' | mimir serve --db memory.db

# Search for it
echo '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"mimir_recall","arguments":{"query":"Hello"}}}' | mimir serve --db memory.db

Why Mimir

Mimir is the only memory engine that is simultaneously MCP-native,local-first, zero-dependency, AND agent-first.

Comparison Matrix

Full comparison: Mimir vs Mem0 →vs Letta →vs Zep →

Stress Test: 100K Entities

Mimir handles production workloads on modest hardware:

Run it yourself: cargo test stress_100k --release -- --ignored --nocapture

Framework Integrations

Ready-to-use adapters that make Mimir the default memory backend forpopular AI agent frameworks:

Each adapter:

• Connects via MCP stdio subprocess (persistent session)
• Maps the framework's memory interface to Mimir tools
• Comes with a README quickstart (5 minutes to working)
• Has passing tests with mocked MCP transport

Any MCP-compatible framework works with Mimir directly. SeeAwesome Mimir for the full list.

43 MCP Tools

Entity CRUD

Search & RAG

Graph

Journal

State

Lifecycle

Quality

Vault & Federation

Metrics & Ops

CLI

# Server
mimir serve --db /data/mimir.db
mimir serve --web --port 8767 --encryption-key ~/.mimir/secret.key
mimir serve --llm-endpoint http://localhost:11434/api/generate --llm-model llama3
mimir serve --transport sse --port 8787 --mcp-token my-secret-token

# Maintenance (operate directly on DB, no server needed)
mimir stats          --db /data/mimir.db
mimir forget         --db /data/mimir.db --category decision --key stale-choice --reason "superseded"
mimir prune          --db /data/mimir.db --category junk --min-decay 0.1 --dry-run
mimir purge          --db /data/mimir.db --dry-run
mimir decay          --db /data/mimir.db
mimir reindex        --db /data/mimir.db
mimir vault-export   --db /data/mimir.db --vault-dir ./export/
mimir vault-import   --db /data/mimir.db --vault-dir ./export/

# Key management
mimir keygen --key-file ~/.mimir/secret.key

Flags

Features

Hybrid Search

• Offline dense search out of the box — a quantized all-MiniLM-L6-v2 model iscompiled into the binary, so semantic recall works with zero config and zeronetwork (no Ollama, no API key, no model download). Build a lean binarywithout it via cargo build --no-default-features.
• FTS5 keyword search with LIKE fallback and Porter stemming expansion
• Dense vector search via cosine similarity on stored embeddings
• Reciprocal Rank Fusion (RRF) — combine keyword + vector results
• Query expansion — automatic stemming variants for broader recall

Memory Lifecycle

• Ebbinghaus decay — memories naturally fade unless retrieved (refresh on access)
• Layer promotion — buffer → working → core based on access frequency
• Automatic archival — stale entities archive; purge to permanently delete + VACUUM
• Always-on entities — pin critical memories for unconditional session injection

RAG & Embeddings

• mimir_ask — natural language Q&A over stored memories via any LLM (Ollama, OpenAI, etc.)
• mimir_embed — generate and store dense vectors via Ollama or OpenAI-compatible /v1/embeddings
• Supports single-entity and batch-category embedding

Encryption

• AES-256-GCM transparent encryption for entity body_json
• Opt-in via --encryption-key flag
• mimir keygen subcommand for key generation
• FTS5 index stays plaintext for search

Web Dashboard

• Built-in Axum HTTP server (mimir serve --web --port 8767)
• Dark-themed dashboard with search, entity table, vis.js graph, timeline
• Default bind: 127.0.0.1 (use --web-bind 0.0.0.0 to expose)
• Separate SQLite connection in WAL mode for concurrent reads

External Connectors

• GitHub issues connector — ingest issues/PRs by repo, rate-limit aware
• File watcher — scan directories for .md/.txt/.json files with content-hash dedup
• YAML-based connector config via --connectors-config

Multi-Transport

• stdio (default) — zero-config, works with any MCP host
• SSE — Server-Sent Events for HTTP-based MCP clients
• HTTP — REST-style MCP endpoint
• Bearer token auth — for SSE/HTTP transports

Perseus Integration

Mimir is the default memory backend for Perseus:

mimir:
  enabled: true
  transport: "stdio"
  command: ["mimir", "serve", "--db", "~/.mimir/data/mimir.db"]
  timeout_s: 30.0
  merge_strategy: "local_first"
  fallback_to_local: true
  context_categories: ["decision", "architecture", "convention"]
  context_limit: 10

Government & Federal Procurement

Mimir is built for government deployment from the ground up.

For federal buyers: See docs/federal-buyers.md forprocurement information, compliance status, and deployment models (air-gapped,on-premises, classified environments).

Perseus Computing LLC is a US-owned small business. SAM.gov registration in progress.NAICS: 541715, 541511, 541512.

License

MIT — see LICENSE.