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MCP verified MIT Self-run

Daedalus

mcp-kinglabsa-daedalus · by KingLabsA

Daedalus — self-evolving, local-first AI coding assistant powered by the Hermes Deep Mind engine: persistent memory, failure immunity, sleep-time compute, causal world model, MoE routing over 23 providers, calibrated confidence. Terminal + Web IDE + VS Code.

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Install

$ agentstack add mcp-kinglabsa-daedalus

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Daedalus

The self-evolving, local-first coding assistant — powered by the Hermes Deep Mind engine.


Daedalus is a coding agent that runs on your own machine and your own models (Ollama local, or any of 24 providers). One engine, three surfaces — a rich terminal, a web IDE, and a VS Code extension — and a cognitive stack no other assistant ships: persistent memory, a failure "immune system", sleep-time compute, judge-verified goals, causal blast-radius prediction, MoE routing, and learned confidence calibration.

It doesn't just chat. It scaffolds runnable full-stack/mobile apps, verifies them, and prepares the deploy.

pip install daedalus-ai
daedalus            # rich terminal UI
daedalus web        # web IDE in your browser
daedalus app        # native desktop window

Why it's different

| | Daedalus | Typical assistant | |---|---|---| | Runs on | your local models (Ollama) + 24 providers | 1–3 cloud APIs | | Memory | persistent across sessions; rebuilds context from checkpoints | forgets each session | | Learns while idle | subconscious dreams/distills into memory & skills | only thinks when prompted | | Stops when done | independent judge must confirm the goal | claims done optimistically | | Before an edit | predicts blast radius from git co-change history | edits blind | | Routing | validated-live MoE across providers, learned calibration | fixed model | | Ships | scaffolds → verifies (eval gate) → deploys | code only |


Install

pip install daedalus-ai                      # from PyPI
# optional extras:
pip install "daedalus-ai[app]"               # native desktop window (pywebview)
pip install "daedalus-ai[browser,desktop]"   # Playwright browser + PyAutoGUI desktop control

From source:

git clone https://github.com/KingLabsA/daedalus.git && cd daedalus
./install.sh

The three surfaces

1. Terminal — daedalus

A rich TUI: streamed tokens, markdown + syntax highlighting, inline diff-approve before writes, @file mentions, input history, Ctrl-C to cancel mid-run. Shows which provider each answer routed to.

Headless one-shot for CI / scripts / git hooks:

daedalus run "fix the failing test" --yes --json
# {"ok": true, "result": "...", "routed_to": "freellmapi", "files_changed": ["test_x.py"]}

2. Web IDE — daedalus web

One process serves the built UI + agent over a token-protected WebSocket. The Cockpit puts everything on one page:

  • Chat with inline changeset review (accept/reject per file or per hunk)
  • Monaco editor with live file tree
  • Terminal (sandboxed command stream) + Preview (live app canvas)
  • ShipBar — one-click Scaffold / Verify / Deploy

Plus a Mind dashboard: memory, subconscious activity, calibration curve, expert routing, blast-radius predictor, device doctor, model advisor.

3. Desktop — daedalus app

A real native window (pywebview → WebKit/WebView2/GTK), not a browser tab and not Tauri. ./build_app.sh produces a self-contained double-clickable Daedalus.app via PyInstaller (bundles Python + agent + UI).

4. VS Code — kinglabs.daedalus-vscode

Chat sidebar + native inline diffs driven by the changeset protocol.


Models — local-first, free-first

Daedalus auto-routes every request (easy → free local model, hard → strongest live provider) and only uses providers that actually answer — keys are validated with a live probe, not just checked for presence.

  • Ollama (recommended): brew install ollama && ollama serve, then ollama pull qwen2.5-coder:7b. Local models are context-capped (HERMES_LOCAL_NUM_CTX, default 8192) and routed through Ollama's native API so num_ctx is honored (avoids an 8B model ballooning to 23 GB).
  • FreeLLMAPI gateway: launch it, set FREELLMAPI_API_KEY.
  • OpenCode Zen: OPENCODE_API_KEY (frontier models via one key).
  • Free cloud tiers: Groq, Google AI Studio, Mistral, Cerebras, DeepSeek — put keys in .env.

daedalus doctor shows exactly which providers are live right now and what's missing. daedalus models shows which models your hardware can run.

Useful env: HERMES_AUTO_ROUTE=off, HERMES_LLM_TIMEOUT=120, OLLAMA_MODEL=, HERMES_SUBCONSCIOUS=off.


The Deep Mind engine (Hermes)

  • Context Engine — persistent memory (SQLite FTS), budgeted injection, checkpoint-based context reconstruction instead of truncation.
  • Failure Immune System — every tool failure becomes a searchable "antibody"; before acting it checks whether it got burned this way before, in this repo.
  • Subconscious — sleep-time compute: consolidates session experience into memory and distills repeated workflows into skills while idle.
  • GoalJudge — an independent model verifies a /goal is truly complete before stopping (fail-open).
  • Causal World Model — mines git co-change history + import graph to predict an edit's blast radius, and warns before high-risk writes.
  • Model Orchestra (MoE) — classifies each task and routes to the best expert; committees + judged Max Mode best-of-N.
  • Epistemic Engine — records predicted confidence vs actual outcomes; cost-aware routing driven by learned calibration.
  • Senses — image analysis, video understanding (ffmpeg frame sampling), voice in/out.
  • Native MCP client — connect any Model Context Protocol server via .hermes/mcp.json.
  • Profile builder — first-launch interview pre-builds persona skill packs (developer, PM, doctor, engineer, …).

Self-* loop: self-learning (record → skill), self-verification (pytest gate), self-correction (errors feed back), self-implementation (writes & registers its own tools).


Text-to-app → verify → deploy

daedalus run "build a tailwind todo app called Tasks" --yes

Scaffold (17 kinds, runnable — not stubs): web · tailwind/shadcn · supabase · next/t3 · astro · svelte · api (FastAPI) · saas/fullstack · cli · mobile/ios/android (Expo) · mcp (a self-extending MCP tool server). Uses the canonical create-* generator when installed, else a built-in skeleton.

Verify (eval gate) — build must pass / code must compile / tests must be green / MCP must handshake. A broken app is blocked from deploying.

Deploy — detects the project, writes the provider config (vercel.json / netlify.toml / fly.toml / eas.json), and hands you the exact commands. Targets: Vercel, Netlify, Fly.io, Expo EAS. (It prepares everything; the authenticated login step is yours.)


Commands (CLI & web)

/goal · /multitask · /kanban · /memory · /remember · /dream · /distill · /subconscious · /blast · /experts · /max · /route · /calibration · /see · /say · /listen · /doctor · /models · /profile · /mcp · /ship · /deploy · /checkpoint · /safety · /provider · /reset — full list via /help.


Architecture

agent_ultimate.py        Think→Act→Observe loop, tool registry, safety
core/
  providers.py           24 providers, MoE-tier router, validated liveness, cost
  server.py              WebSocket protocol (chat, files, changesets, ship/deploy)
  context/               memory, immune system, checkpointer, budgeter
  cognition/             dream, distill, judge, subconscious
  intel/                 code intel, LSP client, embeddings, causal world model
  senses/                MoE orchestra, vision, voice
  epistemic/             calibration, cost router, Max Mode
  platform/              MCP client, doctor, profiler, model advisor
  changeset.py           per-file & per-hunk edit review
  scaffold.py            text-to-app (17 kinds)
  deploy.py / evalgate.py   deploy planning + pre-ship verification
desktop/                 React web UI (Cockpit, Mind, editor)
vscode-extension/        VS Code client
bench/swebench_runner.py SWE-bench harness

Standalone core/* packages import nothing from the monolith; the monolith re-exports for back-compat. 291 offline tests, CI on macOS + Linux × Python 3.11–3.13, ruff-clean.


Development

pip install -e ".[dev]"
python -m pytest tests/ -q          # offline suite (291)
python -m ruff check .              # lint gate
cd desktop && npm install && npm run build   # web UI

Contributions welcome — see [CONTRIBUTING.md](CONTRIBUTING.md). Security policy in [SECURITY.md](SECURITY.md).


Status & honest notes

  • Positioning: single-user, local-first by design (not multi-tenant/SaaS).
  • Desktop: the pywebview daedalus app is the recommended standalone; the legacy Tauri path is parked on an upstream macOS bug.
  • Benchmarks: a SWE-bench harness ships in bench/, but no score is published yet — run it locally with a strong provider before quoting one.

License

MIT © KingLabs. Product: Daedalus. Engine: Hermes.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.