mateaix/mateclaw
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba. observed · 2026-09-03
Health v2 · maintenance only
82/100
- Activity 100
- Release rhythm 99
- Longevity 10
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 9.0
- age_days: 151
- days_rel: 4
- days_push: 0
- n_releases_24m: 17
Adoption not part of the score
1072 stars · 322 forks observed · 2026-09-03
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
MateClaw is a self-hosted, team-oriented AI agent platform ('second brain') built on Spring Boot and Spring AI Alibaba, shipped as a single JAR or Docker deployment. It combines multi-agent orchestration (ReAct + Plan-and-Execute on a StateGraph runtime), MCP/ACP tool integration, skills with self-evolution, per-user memory, a wiki with knowledge graphs, and multi-channel messaging (Feishu, DingTalk, WeChat, Telegram, Discord, Slack, WebChat) with enterprise controls like approval gates, audit trails, and multi-vendor model failover.
Use cases
- self-host a team AI assistant with multi-user workspaces
- run multi-agent plan-and-execute workflows with tool calling
- connect an AI agent to DingTalk, Feishu, WeChat, or Telegram
- build a team knowledge base wiki with citations and knowledge graphs
- give AI agents persistent per-user memory
- gate sensitive tool calls behind human approval with audit logs
- route LLM requests across multiple providers with failover
- automate content creation for WeChat official accounts and Xiaohongshu
When to choose
- you need a deployable, auditable AI agent platform your IT/security team can approve
- you want multi-user team workspaces rather than a single-user personal agent
- your team communicates via Chinese enterprise IM platforms like Feishu, DingTalk, or WeChat
- you want a Java/Spring Boot stack with one-JAR deployment and full data control
- you need skills, memory, wiki, and MCP tools unified in one registry with governance
When to avoid
- you want a lightweight personal agent with minimal setup
- you need a Python/TypeScript agent ecosystem rather than Java
- you only need a simple chatbot wrapper around one LLM API
- you require fully managed cloud hosting rather than self-hosting
Facets
application · maturity active
agent-framework chatbot rag mcp chat-interface webhook self-hosted workflow-automation search-engine large-language-models chatbots self-hosted developer-tools messaging-platforms self-hosted cross-platform jvm multi-agent-orchestration plan-and-execute spring-ai-alibaba second-brain team-workspaces approval-gate audit-trail skills memory knowledge-graph wiki dingtalk feishu telegram-bot discord slack wechat model-failover trajectory-replay content-studio ai-agents automation docker web-server desktop
6 sources
- readme: https://github.com/mateaix/mateclaw · fetched 2026-09-03 · f9582a79add1
- homepage: https://claw.mate.vip · fetched 2026-08-29 · 1da4883ab1b3
- site_page: https://claw.mate.vip/docs · fetched 2026-08-29 · c8004106d160
- site_page: https://claw.mate.vip/docs/deepseek-harness · fetched 2026-08-29 · ad9139ad6a85
- site_page: https://claw.mate.vip/docs/zh/desktop · fetched 2026-08-29 · ad9139ad6a85
- site_page: https://claw.mate.vip/docs/zh/quickstart · fetched 2026-08-29 · ad9139ad6a85
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| mateaix/mateclaw | main | 82 |
For agents
markdown · JSON · MCP: product_card(name="mateaix/mateclaw")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem