MUR

The local-first AI agent platform, in native Rust.

Run a fleet of specialized AI agents on the machine you already own — agents that learn from every session, speak with an on-device voice, plug into the AI tools you already use, and can be handed to a friend as a single file.

Quick start · Features · Architecture · CLI · Docs · Website

What is MUR?

Every AI tool you use today is stateless and cloud-tethered: each session starts from zero, and the agent lives in someone else's datacenter. MUR inverts both assumptions.

MUR runs specialized agents as long-lived local processes — each with its own model binding, system prompt, MCP servers, skills, schedule, voice, and permissions — supervised by one small Rust runtime speaking A2A v0.3. On top of the runtime sits a memory pipeline with a maturity lifecycle: what an agent learns in one session is captured, scored, stored as plain YAML, retrieved by hybrid semantic search, and injected into the next session — and it decays when it stops being useful, so no junk accumulates.

You talk to your fleet through the MUR Hub desktop app (chat, approvals, desktop pets), by voice, from an iPhone, from the terminal, or through Slack / Telegram / Jira. And when an agent becomes genuinely useful, you can export it as a signed .muragent file and give it to someone who has never heard of MUR.

In one line: a native-Rust, local-first fleet of specialized AI agents that learn and evolve — light enough to be always-on on the Mac you already own, and each exportable as a companion you can hand to anyone.

Why local-first?

• It fits on your machine. ~200K lines of native Rust — no Electron, no Python sidecar. An always-on fleet plus a local LLM fits in consumer RAM.
• Marginal cost ≈ 0. Inference runs on your hardware. Everything local is free, with no per-token meter.
• Privacy is structural, not a setting. Memory, recordings, telemetry, and voice stay under ~/.mur/. Logs pass through a redaction chokepoint before they touch disk, and a compile-time test forbids the companion module from importing network clients.

How MUR compares

🚀 Quick start

The 5-minute path — MUR Hub (macOS, Apple Silicon)

1. Download MUR-Hub-aarch64-apple-darwin.dmg from the latest release.
2. Drag MUR Hub into Applications and open it.
3. Say hi — the built-in concierge agent MUR is alive immediately: offline, no API key, no signup, running on a bundled local multimodal model.

Received a .muragent file from a friend? Double-click it. Hub verifies the signature, walks you through model setup, and the agent comes alive.

Power users: Hub menu → Install Command-Line Tools… puts mur on your PATH.

The CLI path

# macOS / Linux
curl -fsSL https://mur.run/install.sh | sh

# Windows (PowerShell)
irm https://mur.run/install.ps1 | iex

# Homebrew (macOS arm64)
brew install mur-run/tap/mur

# From source
cargo install mur-core        # installs the `mur` binary

mur init                                      # interactive setup wizard
mur agent create coach --model llama3.2:3b    # create an agent (default provider: ollama)
mur agent install-service coach               # run it as a launchd/systemd user service
mur agent cli coach                           # streaming TUI chat with tool approvals
mur agent cli dev qa ops                      # three agents, tiled panes (tmux/zellij/WezTerm/kitty)
                                              #   --resume continues the last conversation
murmur coach                                  # quick form (murmur symlink), identical to mur agent cli coach

Teach the AI tools you already use

MUR's memory layer works even if you never create an agent — it rides along with Claude Code, Codex, Cursor, Gemini-family CLIs, and a dozen more:

mur init --hooks                              # install hooks for detected AI tools
mur sync                                      # write learned patterns into each tool's native config
mur notes search "how we handle auth errors"  # query your accumulated memory

✨ What can a MUR agent do?

🤖 Run as a real local process

One BusyBox-style runtime binary, one symlink per agent (mur_agent_coach). Each agent owns its model binding (Ollama, MLX, Anthropic, OpenAI, … via the ~/.mur/models.yaml registry), system prompt, MCP servers, skills, keychain-backed secrets, cron schedules, webhook receiver, and a rotating Ed25519 identity. mur agent exposes 40+ subcommands for the full lifecycle — create, chat, export, schedule, permissions, telemetry, trash, rollback.

🧠 Learn — and forget — like a teammate

flowchart LR
    C["capture<br/>significance · feedback"] --> S["store<br/>YAML truth + vector index"]
    S --> R["retrieve<br/>vector 0.7 + BM25 0.3"]
    R --> I["inject<br/>hooks · MCP · prompts"]
    I -.->|next session| C
    E["evolve<br/>decay · maturity · recombination"] <-.-> S

Knowledge moves through a maturity lifecycle driven by real usage, with decay half-lives by tier (session 14d / project 90d / core 365d):

stateDiagram-v2
    direction LR
    [*] --> Draft
    Draft --> Emerging: validated by usage
    Emerging --> Stable: repeated wins
    Stable --> Canonical: proven over months
    Canonical --> Stable: unused — decay
    Stable --> Emerging: unused — decay

Recurring tool sequences across sessions are mined into suggested workflows (mur workflow suggest) — no drag-and-drop DAG editor, no marketplace; your own recorded behavior is the authoring tool.

Capture is ambient: once hooks are installed, every session is recorded locally (scrubbed at write, retention-GC'd, one line of config to turn off). mur in just marks the current session as important; mur out reviews the workflow proposals MUR harvested from your recent sessions — accept one and it becomes a draft workflow you can run with mur run.

💬 Be everywhere you are

• MUR Hub — multi-conversation rail across the fleet, streaming replies, human-in-the-loop tool approvals, dashboards, and drag-out desktop pets with expressions and speech bubbles.
• Voice — fully on-device TTS (Kokoro 82M) + STT (whisper.cpp); respects Do Not Disturb, Focus, and a busy microphone.
• iPhone — the in-repo iOS companion (mur-mobile-app) pairs over LAN with mur agent pair (QR); off-LAN traffic falls back to a relay that forwards only end-to-end-signed envelopes. All AI stays on your Mac.
• Watch together — agents open videos in VLC, explain the current scene, analyze whole videos with timestamps, and (opt-in) comment on scene changes — on a local multimodal model.
• Bridges — Slack, Telegram, Jira (@mur implement PROJ-123), and webhooks.

🎁 Be given away

flowchart LR
    A["Your agent<br/>in Hub or CLI"] -- "Share /<br/>mur agent export" --> B["coach.muragent<br/>signed · sanitized · data-only"]
    B -- "any channel" --> C["Friend<br/>double-clicks"]
    C --> D["Hub verifies signature,<br/>guides model setup"]
    D --> E["Agent alive<br/>on their machine"]

The .muragent package is DSSE-signed and contains no executable code and no secrets — private keys and API keys are stripped at export. The recipient installs MUR Hub once (signed + notarized); after that, agents travel as plain files.

🔐 Stay governed

• Kernel sandbox per OS — Landlock + seccomp (Linux), SBPL (macOS), Job Object (Windows) — plus a DNS-resolver guard that filters network egress.
• Human-in-the-loop — tool calls pause for your approval in Hub and in mur agent cli (opt out per session with --auto).
• Deletion safety — destructive file actions go through a trash with a cancel window and explicit restore (mur agent trash); nothing is hard-deleted on a timer.
• Auditability — every action lands in an append-only JSONL ledger; MUR Commander (companion crate) adds an Ed25519-signed constitution and a hash-chained audit log for cross-network fleets.

🔌 Power the tools you already pay for

Three integration layers, by interaction shape:

Synced tools include Claude Code, Gemini CLI, Auggie, Cursor, Copilot CLI, OpenClaw, OpenCode, Amp, Codex, Aider, Windsurf, Zed, Junie, Trae, Cline, and Amazon Q. The compression tools (mur_compress / mur_retrieve) shrink large payloads 40–80%, reversibly — originals stay retrievable by hash.

🦀 Architecture

MUR Commander — the cross-network orchestration, governance, and evaluation plane — ships as a separate crate.

On disk, everything lives under ~/.mur/: agents, skills, notes, and workflows as human-readable, git-friendly YAML (the source of truth), plus a LanceDB vector index that is always rebuildable (mur internals reindex). No opaque database lock-in.

🧰 CLI at a glance

mur daemon serve     # web dashboard at http://localhost:3847
mur dashboard        # terminal TUI dashboard

mur
├── init / doctor / update / stats / verify
├── agent        create · cli · send · card · export · install · companion · voice ·
│                pair · schedule · perm · secret · trash · queue · rollback … (40+)
├── skill        install · search · show · generate · suggest · evolve · recombine ·
│                publish · audit · trust · exchange · drafts · eval …
├── notes        create · search · list · show
├── workflow     run · suggest · list · schedule · show · search · new · publish · install
├── session      start · stop · record · status · list · review · show · export · push
├── sync         (16+ AI tools) · status · fleet pull/push/both
├── hook         unified hook entry for AI tools (prompt / tool / stop / session-start)
├── chat         conversations archive + ask
├── model        add · list · show · remove · migrate
├── source       external knowledge — Obsidian · Notion · Joplin
├── project      index · search   (semantic code search)
├── daemon       start · stop · status · serve · sleep
├── auth         login · logout
├── team         shared skills (private registries)
├── push / fetch signal outbox / inbox ↔ server
├── deploy       Docker Compose deployment
└── internals    low-level store access · reindex

🔨 Build from source

git clone https://github.com/mur-run/mur.git && cd mur

cargo build --workspace          # debug build (GUI apps are workspace-excluded)
cargo nextest run --workspace    # tests (CI uses nextest)
cargo clippy --workspace -- -D warnings

./build.sh                       # release build with the embedded web dashboard
./install.sh                     # build + install to /opt/homebrew/bin/mur

The two Tauri apps (mur-hub-gui, legacy mur-agent-gui) build from their own manifests so the workspace build never pulls WebKitGTK / Cocoa / WebView2. The iOS app builds with mur-mobile-app/build-ios.sh.

🧭 Roadmap

• Cost-Router orchestrator — route the easy ~80% of sub-tasks to local models and spawn a frontier coding agent (claude / codex / agy) only for the hard parts, as governed, sandboxed subprocesses. Spec merged; router in progress.
• Fleet Sync (Pro) — replicate your evolved fleet (profiles, skills, workflows, and their maturity/lifecycle state) across devices. Everything local stays free.
• Hub on Windows / Linux, and an Android companion from the same Rust mobile core.

Want to teach an agent something new? See Authoring Skills.

Design history lives in docs/superpowers/specs/ and docs/architecture/runtime-overview.md.

🤝 Contributing

Issues and PRs are welcome — see CONTRIBUTING.md.

cargo nextest run --workspace && cargo clippy --workspace -- -D warnings

📄 License

MIT