MateClaw

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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.

Three things that make it different

1 · Your AI doesn't die when a model does

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.

2 · Knowledge that links itself

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.

3 · One product, five surfaces

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

What's in the box

Digital employees, not chatbots

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.

Knowledge & memory

• 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

Skills · MCP · ACP — three ways to extend capability

• 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

Business orchestration (1.3.0+)

• 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

You see what every employee is doing

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.

Multimodal creation

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.

Enterprise-ready

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.

AI is becoming infrastructure

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.

Why MateClaw