Ross ROSS = Recommend OSS · open-source software intelligence for agents

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

github.com/mateaix/mateclaw · homepage · Java · Apache-2.0 (permissive) 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

Full methodology

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

Member repositories

RepositoryRoleHealth v2
mateaix/mateclawmain82

For agents

markdown · JSON · MCP: product_card(name="mateaix/mateclaw")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem