Other personal AI agents are built for one person. MateClaw is the one your IT department can actually sign off on.

Multi-user workspaces. Approval-gated sensitive actions. Full audit trail. Spring Boot Actuator health monitoring. Per-channel error isolation so one chat platform's outage doesn't take down the rest. One JAR on your own machine, zero data egress.

And underneath, a real agent harness. ReAct + Plan-and-Execute on a StateGraph runtime — not a one-shot RAG call dressed up. Tools, Skills, MCP, and ACP converge on one registry with per-employee binding. Sensitive tool calls flow through an approval gate you can actually inspect. Multi-vendor failover keeps the loop running when a provider doesn't.

Most AI tools die when their vendor has a bad day. Most forget you the moment the tab closes. Most give you a chatbox and call it a product.

MateClaw is the whole widget. One deployment. Reasoning, knowledge, memory, tools, channels — built together, not bolted on. And when your primary model goes down, the next one picks up mid-sentence.

Primary key expired. Vendor returns 401. Network blip. Quota drained.

Other tools hand you a red error card. MateClaw routes to the next healthy provider — DashScope, OpenAI, Anthropic, Gemini, DeepSeek, Kimi, Ollama, LM Studio, MLX, 14+ in total — and the user sees the reply finish. A provider health tracker parks bad vendors in a cooldown window so they don't waste seconds on every turn.

You don't write a retry script. You drag providers into priority order in Settings → Models and watch the health dashboard fill with green dots as requests route around failures in real time.

Upload a PDF, a batch of markdown, a scraped page — raw material in.

MateClaw's LLM Wiki digests it into structured pages, builds [[links]] between them, and remembers where every sentence came from. Click a citation, see the exact source chunk. Ask a question, the page you get is stitched from the right chunks — with references you can verify.

This is the difference between a warehouse and a library.

Same brain. Same memory. Same tools. Different doors.

$0 · No tokens metered. No seats billed. Your server. Your data. Your keys.

You hire coworkers, not chat boxes. Each one has a Role, a Goal, a Backstory, a pixel-art avatar, and a color of their own — five career templates ship ready (Product Researcher · Customer Support · Knowledge Curator · Data Analyst · Executive Assistant). ReAct drives iterative reasoning, Plan-and-Execute decomposes complex multi-step work, employees can delegate to one another in parallel. Dynamic context pruning, smart truncation, stale-stream cleanup — the boring stuff that makes long conversations actually work.

• LLM Wiki — raw materials digest into linked pages with citations; the hot cache auto-injects into every employee's system prompt. Transformations engine (1.3.0+) turns the Wiki from a search index into a processing pipeline
• Workspace memory — AGENTS.md, SOUL.md, PROFILE.md, MEMORY.md, daily notes
• Memory lifecycle — post-conversation extraction, scheduled consolidation, Dreaming workflows. Workflows can also write directly into an employee's MEMORY.md via the write_memory step

• SKILL.md packages — manifest + prompt + tool list + LESSONS.md (gets smarter the more you use it). Eight starter templates plus a five-step creation wizard, with Pre-flight checks that tell you what's missing before install
• MCP — stdio / SSE / Streamable HTTP, plug into any external tool server. Per-employee binding (1.3.0+) means a tool you install for one employee doesn't bleed into another's toolbox
• ACP — bring top-tier coding agents like Claude Code and Codex in as employees, auto-bridged to skill cards with wrapper tools
• Tool Guard — RBAC + approval flow + path protection. Capability needs boundaries

• Workflow — compose multiple employees plus system actions (approval / channel dispatch / write-memory) into a publishable, triggerable, replayable linear DSL. Seven step modes (sequential / fan_out / collect / conditional / await_approval / dispatch_channel / write_memory). JSON-first authoring with Monaco + schema validation, or natural-language → draft generation
• Triggers — wire system events to workflows or to employee conversations. Six pattern types (cron / webhook / channel_message / agent_lifecycle / content_match / workflow_completion). Default-on event governance: dedup, per-trigger rate limit, bot-self filter, recursion guard, fail-closed unknown patterns
• Wiki Transformations — Wiki stops being retrieval-only. User-authored templates run against raw materials or existing pages, with cross-material map-reduce aggregation, reverse-citation extraction, JSON output mode, and per-template model picker

Admin Runtime Console (Settings → System → Runtime) — who's running, what step they're on, how many tokens, one-click force-recycle when stuck. Streaming is staged honestly (thinking / tool / answer), per-event SSE IDs make reconnects safe, multi-employee delegation no longer fights itself, long tasks demand evidence-grounded answers.

Text-to-speech · Speech-to-text · Image · Music · Video · 3D. First-class, not add-ons. Sidecar routing (1.3.0+) means a text-only main model + an image attachment no longer dead-ends — a configured vision model describes the image, and the main model answers. Image edit lands too: refer to an earlier conversation attachment by msg:<id>:<idx> and ask the model to recolor or restyle it. Four document-generation tools (DocxRenderTool / XlsxRenderTool / PptxRenderTool / PdfRenderTool) render Markdown straight to Office files inside the JVM — no subprocess, no Office install.

RBAC + JWT. Personal Access Tokens for headless scripts and CI. HMAC-SHA-256 outbound webhook signing. Distributed Cron lock so multi-instance deployments don't double-fire. Full audit trail. Flyway-managed schema that auto-heals on upgrade. One JAR to ship. MySQL in production, H2 for dev — nothing to change in your code.

On March 2, 2026, Claude went dark for 4 hours across API, web, and mobile. Three weeks later, another 5 hours. Every company that bet their AI strategy on a single vendor spent those outages staring at red error cards.

This is the same shift databases went through around 2010 and cloud went through around 2018: the winning layer stops being tied to one supplier. 57% of companies now run AI agents in production. None of them want one vendor's bad day to become their bad day.

MateClaw is that layer — built the Spring Boot way.

OpenClaw and Hermes Agent are excellent personal AI platforms — pick either if you're running one user on one laptop, building your own agent from CLI, and treating everything as config files to hand-tune. Both have bigger communities than MateClaw today.

MateClaw is the version built for teams. RBAC per digital employee, per model, per tool. An approval flow that pauses risky actions for review. Full audit trail. The Admin Runtime Console gives one operator real-time visibility into 50 employees running across 14 vendors — stuck? force-recycle in one click. Spring Boot inside — drop-in for any Java shop already running production services.

Same "whole widget" philosophy. Different center of gravity.

# Backend
cd mateclaw-server
mvn spring-boot:run           # http://localhost:18088

# Frontend
cd mateclaw-ui
pnpm install && pnpm dev      # http://localhost:5173

Login: admin / admin123

cp .env.example .env
docker compose up -d          # http://localhost:18080

Download from GitHub Releases. Bundles JRE 21. No Java install needed.

mateclaw/
├── mateclaw-server/        Spring Boot 3.5 backend (Spring AI Alibaba, StateGraph runtime)
├── mateclaw-ui/            Vue 3 + TypeScript admin SPA (built into the server JAR)
├── mateclaw-webchat/       Embeddable chat widget (UMD / ES bundles)
├── mateclaw-plugin-api/    Java SDK for third-party capability plugins
├── mateclaw-plugin-sample/ Reference plugin implementation
├── docker-compose.yml
└── .env.example

Desktop binaries ship via GitHub Releases with a bundled JRE 21 — no Java install needed.

Full docs at claw.mate.vip/docs — setup, architecture, each subsystem, API reference.

v1.3.0 (shipped 2026-05-13) — Workflow engine · 6-pattern trigger system · Wiki transformations · per-agent MCP binding · multimodal sidecar routing · four JVM-native document generation tools · image edit. See the v1.3.0 release notes for the full story.

Next — Drag-to-edit workflow canvas · run replay timeline · loop and invoke_skill step modes · trigger priorities and event replay · industry scenario marketplace · more ACP upstream integrations.

git clone https://github.com/matevip/mateclaw.git
cd mateclaw
cd mateclaw-server && mvn clean compile
cd ../mateclaw-ui && pnpm install && pnpm dev

Mate is companion. Claw is capability.

Something that stays with you — and grabs work and moves it.

Apache License 2.0. No asterisks.