# Overhuman > Self-evolving AI daemon in Go with fully generative UI. LLM generates unique HTML/ANSI interfaces from scratch for every response — not templates, not component catalogs. 10-stage pipeline, 4-level reflection, fractal agents, auto-generated code skills, 6 input channels. - **Type:** MCP server - **Install:** `agentstack add mcp-aladin2907-overhuman` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [aladin2907](https://agentstack.voostack.com/s/aladin2907) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [aladin2907](https://github.com/aladin2907) - **Source:** https://github.com/aladin2907/overhuman ## Install ```sh agentstack add mcp-aladin2907-overhuman ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About       Overhuman is an always-on AI daemon that processes tasks through a 10-stage pipeline and generates a unique visual interface for every response — not from templates, but from scratch. It learns from repetition, auto-generates code skills that replace LLM calls, and gets cheaper with every request. Spec · GenUI Spec · Architecture · Phases · Quick Start Kiosk companion display — pipeline HUD, neural canvas, metrics panel, theme controls. Pure Go, zero JS frameworks. --- ## 🎨 Generative UI — The Core Feature Most AI assistants return plain text. Some pick from pre-built component catalogs. **Overhuman generates complete UI from scratch for every response.** ``` "Analyze server logs" → Interactive dashboard with latency charts, error heatmap, filterable table "Compare Q1 vs Q2" → Side-by-side cards with sparklines and delta highlights "Draft an email" → Rich editor with tone slider and preview pane "Explain this code" → Syntax-highlighted walkthrough with collapsible sections ``` No component registry. No JSON schema. The agent decides the best visualization — charts, tables, forms, games, timelines — whatever fits the data. ### Where Overhuman sits in the ecosystem ``` Agent Freedom ▲ │ Level 3 ─── Fully ┌───┴────────────────────┐ Generated │ Cloud AI Generators │ │ AI Sandbox Tools │ │ ★ OVERHUMAN │ └────────────────────────┘ │ Level 2 ─── Declarative │ Declarative JSON UI │ Server-Driven UI │ Level 1 ─── Controlled │ Component Libraries │ Transport Layers │ ───────────────┴─────────────────────► Safety Low High ``` > [!NOTE] > **Level 1-2** limit the agent to what a developer pre-built. **Level 3** means infinite UI surface — the agent can create any visualization it can imagine. The tradeoff is sandboxing (solved) and non-determinism (solved via self-healing + reflection). Research confirms LLMs are effective UI generators, achieving ELO 1710 against human-crafted designs ([paper](https://generativeui.github.io/)). ### Three rendering targets **🖥️ Terminal** ANSI escape codes + box drawing *CLI over SSH, no browser* **🌐 Browser** HTML + CSS + JS via WebSocket *Sandboxed iframe — no data leak* **📺 Kiosk** Full-screen SPA on any screen *Tablet / wall mount / desktop* ### Kiosk: the companion display A full-screen web app designed for a dedicated screen — tablet on your desk, monitor on the wall, or a browser window you keep open. - **Pipeline HUD** — real-time progress through all 10 stages - **Generated UI** — each response as a rich HTML app in sandboxed iframe - **Neural canvas** — animated particles that react to pipeline activity - **Agent status ring** — visual daemon heartbeat - **Metrics panel** — tasks, skills, memory entries - **Theme system** — sci-fi · cyberpunk · clean - **Sound engine** — Web Audio API synthesis (zero files) - **CRT mode** — scanlines + glow for retro aesthetic > [!TIP] > **Device-adaptive**: phone → essentials only (no HUD, overlay sidebar) · tablet → control pad · desktop → full command center. ### Self-healing UI ``` LLM generates HTML ──→ Render in sandbox ──→ Error? │ ┌─── Yes ─────────┤ │ └─── No ──→ Track interactions ▼ (clicks, scrolls, ignores) Feed error to LLM │ Retry (max 2) ▼ │ Feed back into generation Still broken? │ ├─ Yes → Plain text fallback ▼ └─ No → Serve healed UI Next UI is better ``` > UI generation cost: ~$0.001 (gpt-4.1-nano). Skipped for short text answers. --- ## ⚙️ How It Works ```mermaid graph LR A[📡 Input] --> B[1 Intake] B --> C[2 Clarify] C --> D[3 Plan] D --> E[4 Agent] E --> F[5 Execute] F --> G[6 Review] G --> H[7 Memory] H --> I[8 Patterns] I --> J[9 Reflect] J --> K[10 Go Live] K --> L[🎨 GenUI] K --> M[💾 Skills] style A fill:#00d4aa,stroke:#333,color:#000 style L fill:#7c3aed,stroke:#333,color:#fff style M fill:#3fb950,stroke:#333,color:#000 ``` Every request passes through the full 10-stage pipeline. Stages 7-9 feed back into the system — this is how Overhuman learns: **🧠 Memory** — stores results in short-term + long-term (SQLite FTS5) **🔁 Patterns** — fingerprints recurring tasks **🪞 Reflection** — 4 levels of self-improvement: | Level | When | Does | |-------|------|------| | Micro | Each step | Adjusts next step | | Meso | Each task | Updates skills | | Macro | Every N tasks | Reevaluates strategies | | Mega | Rarely | Evaluates reflection itself | **⚡ Self-learning** — the killer loop: ``` Task repeated 3x │ ▼ Generate code skill from accumulated examples │ ▼ Register as deterministic alternative to LLM call │ ▼ Next occurrence → code (ms, not seconds. Free, not $0.01) │ Code breaks? → auto-fallback to LLM ``` --- ## ⚡ Features 📡 **6 Input Channels** CLI · Telegram · Slack · Discord · Email · HTTP API 🤖 **Any LLM Provider** OpenAI · Claude · Ollama · Groq · Together · OpenRouter 🧠 **Memory System** Short-term + long-term (FTS5) + pattern tracking 🔄 **Self-Learning** 3x repeat → auto code skill → LLM replaced 🛠️ **20 Skills** Code gen, search, translate, summarize, email + stubs 🌳 **Fractal Agents** Tree hierarchy, delegation, best-of-N, per-agent memory 🪞 **4-Level Reflection** Micro → Meso → Macro → Mega improvement loop 🔐 **Security-First** AES-256-GCM · injection protection · audit trail · sandbox ⏰ **Always-On Daemon** OS service (launchd/systemd) · heartbeat · proactive goals 🔌 **MCP Tools** Model Context Protocol for external tool integration --- ## 🚀 Quick Start ```bash # Build go build -o overhuman ./cmd/overhuman/ # Configure (interactive wizard — provider, API key, model) ./overhuman configure # Chat mode ./overhuman cli # Or: daemon with HTTP API + WebSocket + Kiosk UI ./overhuman start ``` > [!TIP] > **Zero-config local mode** — no API key needed: > ```bash > LLM_PROVIDER=ollama ./overhuman cli > ``` ### Try it ```bash # Start daemon ./overhuman start # Send a task curl -s http://localhost:9090/input/sync \ -H "Content-Type: application/json" \ -d '{"payload": "What is the capital of France?"}' # Open Kiosk companion display open http://localhost:9092 ``` --- ## 🖥️ Deployment ```bash overhuman doctor # diagnostics overhuman install # install as OS service overhuman status # check daemon overhuman stop # graceful shutdown overhuman logs # tail last 50 lines overhuman update # check & apply (SHA256 verified) overhuman uninstall # remove OS service ``` | Port | Service | Description | |:----:|---------|-------------| | `9090` | **HTTP API** | REST (`/input`, `/input/sync`, `/health`) | | `9091` | **WebSocket** | Real-time UI streaming (RFC 6455, pure stdlib) | | `9092` | **Kiosk** | Full-screen companion display | > File drop: `~/.overhuman/inbox/` — daemon picks up automatically. > Logs: stdout + `~/.overhuman/logs/overhuman.log`. --- ## 🧩 Supported LLMs | Provider | API Key | Models | |----------|:-------:|--------| | **OpenAI** | Required | o3, o4-mini, GPT-4.1 | | **Anthropic Claude** | Required | Claude Sonnet, Haiku, Opus | | **Ollama** | — | Local models (llama3, mistral, etc.) Free | | **LM Studio** | — | Local models via GUI | | **Groq** | Required | Fast inference (Llama, open-source models) | | **Together AI** | Required | Open-source models hosted | | **OpenRouter** | Required | All models through a single key | | **Custom** | Optional | Any OpenAI-compatible server | --- ## 🏗️ Technical Decisions | Decision | Choice | Why | |----------|--------|-----| | Language | **Go** | Daemon-first, goroutines, single binary 15MB, 📁 Project Structure — 21 packages, single binary ``` cmd/overhuman/ — entry point (daemon, CLI, configure, doctor) internal/ ├── soul/ — agent identity (markdown DNA, versioning) ├── agent/ — fractal agent hierarchy ├── pipeline/ — 10-stage orchestrator + DAG executor ├── brain/ — LLM integration, model routing, context assembly ├── senses/ — input channels (CLI, HTTP, Telegram, Slack, Discord, Email) ├── instruments/ — skill system (LLM/Code/Hybrid), code generator, Docker sandbox ├── memory/ — short-term + long-term memory + patterns + shared knowledge base ├── reflection/ — 4 levels of reflection ├── evolution/ — fitness metrics, A/B testing, skill culling ├── goals/ — proactive goal engine ├── budget/ — cost control, limits, budget-based routing ├── versioning/ — versioning with auto-rollback on degradation ├── security/ — sanitization, audit, encryption, validation ├── mcp/ — MCP client and registry (JSON-RPC 2.0) ├── storage/ — persistent KV store (SQLite, FTS5, TTL) ├── genui/ — generative UI (LLM → ANSI/HTML, self-healing, reflection) ├── deploy/ — PID management, OS service templates, auto-update ├── skills/ — 20 starter skills └── observability/ — structured logs and metrics ``` ⚙️ Configuration — environment variables (override config.json) ``` ANTHROPIC_API_KEY — Claude key OPENAI_API_KEY — OpenAI key LLM_PROVIDER — provider: openai, claude, ollama, groq, together, openrouter, custom LLM_API_KEY — key for any provider LLM_MODEL — default model LLM_BASE_URL — URL for custom/ollama OVERHUMAN_DATA — data directory (default ~/.overhuman) OVERHUMAN_API_ADDR — API address (default 127.0.0.1:9090) OVERHUMAN_NAME — agent name ``` --- ## 🌐 HTTP API ```bash # Async (fire-and-forget) curl -X POST http://localhost:9090/input \ -H "Content-Type: application/json" \ -d '{"payload": "Analyze this CSV file", "sender": "user1"}' # Sync (waits for response) curl -X POST http://localhost:9090/input/sync \ -H "Content-Type: application/json" \ -d '{"payload": "Translate to French: Hello world"}' # Health check curl http://localhost:9090/health ``` --- ## 🧪 Tests ```bash go test ./... # 981 tests, 21 packages go test ./... -race # race condition checks ``` All tests run with a mock LLM server — no API keys needed. --- ## 📚 Docs | Document | Description | |----------|-------------| | [`docs/SPEC.md`](docs/SPEC.md) | Full specification (700+ lines) | | [`docs/SPEC_DYNAMIC_UI.md`](docs/SPEC_DYNAMIC_UI.md) | Generative UI specification (1186 lines) | | [`docs/PHASES.md`](docs/PHASES.md) | Implementation tracker | | [`docs/ARCHITECTURE.md`](docs/ARCHITECTURE.md) | Architecture overview | --- MIT License · Contributing ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [aladin2907](https://github.com/aladin2907) - **Source:** [aladin2907/overhuman](https://github.com/aladin2907/overhuman) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** yes - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-aladin2907-overhuman - Seller: https://agentstack.voostack.com/s/aladin2907 - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.