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MIST e4dd08b5f4
feat(agent): 注意力锚定与环境感知——MCP 工具溯源 + skill 约束固定 + 事件通知 (#490)
* feat(agent): 注意力锚定与环境感知——MCP 工具溯源 + skill 约束固定 + 事件通知

## 背景

1. **MCP 工具跨服务器混淆**:MCP 工具名是 `mcp_<serverId>_<slug>_<hash6>`,serverId 是 19 位不可读 Snowflake。LLM 在多服务器任务中常把 slug 拼到错误 serverId 上重构出不存在的工具名,反复重试到 max iterations。
2. **长对话中 skill 约束丢失**:`load_skill` 返回的 SKILL.md 正文存在 messages 历史窗口里,被压缩管线(Soft Trim / Hard Clear / Pre-Prune / LLM Summary)销毁,约束彻底消失,agent 后续步骤违反约束。
3. **运行时环境变更对 agent 不可见**:MCP 服务器断连 / skill 更新发生在 agent 推理中途时,工具列表是 turn-start 快照,LLM 无法感知,继续调用已失效的工具。
4. **ledger 条目可被 LLM 反向覆盖**:Java 用 `auto_`/`pin_` 前缀让位给 LLM,但 LLM 没有反向保护——`progress_update(stepKey="auto_read_file")` 会覆盖 Java 写入的条目,保护是单向的。
5. **SkillManifestParser 从未填充 constraints 字段**:`KNOWN_KEYS` 未列入 `"constraints"`,导致约束被静默路由到 `extras`,所有依赖 `manifest.getConstraints()` 的代码都是死代码。

## 改动内容

### 文件改动

**新增文件(生产代码 4 个)**
- **`mateclaw-server/.../agent/runtime/EnvironmentNotification.java`** — 环境变更通知 record(type / message / timestamp)。
- **`mateclaw-server/.../agent/runtime/RunningConversationRegistry.java`** — 跟踪活跃会话 + 每会话有界通知队列(上限 10)+ TTL 定时清理(30 分钟未活跃的 handle 自动回收)。
- **`mateclaw-server/.../agent/runtime/EnvironmentEventRouter.java`** — 5 个 `@EventListener` 把 MCP/skill 事件翻译成中文 LLM 通知并广播。
- **`mateclaw-server/.../skill/event/SkillUpdatedEvent.java`** — skill 更新/启用/禁用/重扫描事件。

**新增文件(测试 5 个)**
- **`mateclaw-server/.../skill/manifest/SkillManifestConstraintsParsingTest.java`** — constraints 解析白盒测试(5 用例)。
- **`mateclaw-server/.../agent/progress/ProgressLedgerPrefixGuardTest.java`** — 前缀守卫 + 三类条目 + 并发 + 批量 auto-record 白盒(22 用例)。
- **`mateclaw-server/.../agent/runtime/RunningConversationRegistryTest.java`** — registry + router 生命周期 + TTL 清理白盒(24 用例)。
- **`mateclaw-server/.../agent/context/ContextCompressionLedgerSurvivalTest.java`** — 三类条目压缩存活黑盒(5 用例)。
- **`mateclaw-server/.../agent/graph/node/EnvironmentNotificationRenderingTest.java`** — 事件→通知→LLM 可见黑盒(14 用例)。

**修改文件(生产代码 14 个)**
- **`mateclaw-server/.../agent/progress/ProgressLedger.java`** — 增加 `pinned` map + `AUTO_RECORDED_PREFIX` 常量 + 三类条目区分;`mostRecentUpdate` 只看 regular 条目;`renderStaleReminder` 补 pending 计数。
- **`mateclaw-server/.../agent/progress/ProgressLedgerService.java`** — JSON 格式升级为 wrapper `{entries, pinned}`(向后兼容旧 flat-map);`upsert` 加 `auto_`/`pin_` 前缀守卫;`upsertPinned` / `upsertAutoRecorded` / `clearPinnedByPrefix` / `upsertAutoRecordedBatch`(批量版,一次 lock+load+save 处理 N 个工具响应);auto-recorded 4 参签名避免跨服务器键碰撞,有界=5。
- **`mateclaw-server/.../agent/graph/node/ActionNode.java`** — `load_skill` 后 `pinSkillConstraints` 把约束写入 pinned;工具调用后 `autoRecordToolCalls` 收集批量后一次 `upsertAutoRecordedBatch`(避免 N 次 lock+save 串行化);setter 注入保持测试构造器兼容。
- **`mateclaw-server/.../agent/graph/node/ReasoningNode.java`** — C4 注入:drain 通知 → `renderEnvironmentNotifications` → SystemMessage 加入 nonHistoryPrefix;helper 改 package-private 供黑盒测试。
- **`mateclaw-server/.../agent/AgentGraphBuilder.java`** — 系统提示增加 ProgressLedger Discipline 段(agent-3)+ Environment Change Notifications 段(agent-1);SkillCatalog 渲染器扫描约束加 🔒 锚点(agent-4);wire ActionNode setter + ReasoningNode registry。
- **`mateclaw-server/.../agent/AgentService.java`** — `withLifecycleSync` / `withLifecycleFlux` 入口 `safeRegister`、出口 `safeUnregister`,覆盖 Flux 抛错路径。
- **`mateclaw-server/.../skill/manifest/SkillManifest.java`** — 增加 `constraints` 字段(List<String>)。
- **`mateclaw-server/.../skill/manifest/SkillManifestParser.java`** — `KNOWN_KEYS` 加 `"constraints"`;builder 链加 `.constraints(stringList(fm.get("constraints")))`。
- **`mateclaw-server/.../skill/service/SkillService.java`** — 4 个改动点发布 `SkillUpdatedEvent`(rescan / update builtin / update non-builtin / toggle enable-disable)。
- **`mateclaw-server/.../tool/builtin/ProgressLedgerTool.java`** — `@Tool` 描述声明 `auto_`/`pin_` 前缀保留;`@ToolParam stepKey` 同步警告。
- **`mateclaw-server/.../tool/mcp/runtime/PrefixedNameToolCallback.java`** — 新增 3 参构造器,serverName 非空时描述前缀 `[MCP server: <name>]`,让 LLM 区分跨服务器同名工具。
- **`mateclaw-server/.../tool/mcp/runtime/McpClientManager.java`** — `wrapServerCallbacks` 透传 serverName 到 PrefixedNameToolCallback。
- **`mateclaw-server/.../agent/context/ConversationWindowManager.java`** — `PRUNE_EXEMPT_TOOLS` 加入 `load_skill`(A1)。
- **`mateclaw-server/.../agent/graph/executor/ToolExecutionExecutor.java`** — 工具不存在时 `buildMcpAwareNotFoundMessage` 跨服务器搜索同 slug/hash 候选,给出 ≤5 个建议名。

**修改文件(测试 1 个)**
- **`mateclaw-server/.../agent/progress/ProgressLedgerStaleReminderTest.java`** — 回归适配:reminder 文本现在包含 `pending` 计数。

### 测试

- `mvn -pl mateclaw-server -am test -Dtest='SkillManifestConstraintsParsingTest,ProgressLedgerPrefixGuardTest,RunningConversationRegistryTest,ContextCompressionLedgerSurvivalTest,EnvironmentNotificationRenderingTest,ProgressLedgerStaleReminderTest'`:70/70 通过
- `mvn -pl mateclaw-server -am test`(全量回归,含上面 6 个 + 12 个深挖影响类):0 失败 0 错误

### 安全性

- **前缀保留**:`ProgressLedgerService.upsert` 拒绝 `auto_`/`pin_` 前缀,LLM 无法覆盖 Java 管理的条目;`@Tool` 描述显式声明保留前缀。
- **事件路由异常隔离**:`EnvironmentEventRouter.broadcast` 全 try/catch,路由失败永不冒泡到 Spring 事件总线。
- **并发安全**:registry 用 `ConcurrentHashMap` + `ConcurrentLinkedQueue`;ledger upsert 用 per-conversation `ReentrantLock`;批量 auto-record 在单次 lock 内完成;`ProgressLedgerPrefixGuardTest.concurrentUpsertAndAutoRecordAreSafe` 锁定。
- **内存有界**:通知队列每会话上限 10(LRU 驱逐最老);auto-recorded 条目每会话上限 5(驱逐最老);registry 后台 TTL 清理(30 分钟未活跃的 handle 自动回收)。
- **绑定机制不受影响**:MCP/skill 的 agent 绑定(`mate_agent_tool` / `mate_agent_skill` 表)完全未被触碰;C3 通知广播是有意全量(非按 agentId 过滤),最坏情况是无关 agent 多收一条 SystemMessage(LLM 被告知"如无关可忽略")。

## 逐项验证

### 改动 1:SkillManifestParser 真正解析 constraints(深挖修复)

**文件**:`mateclaw-server/src/main/java/vip/mate/skill/manifest/SkillManifestParser.java:33-47,108`

| 项 | 内容 |
|---|---|
| 改了什么 | `KNOWN_KEYS` 集合加入 `"constraints"`;builder 链加入 `.constraints(stringList(fm.get("constraints")))`。 |
| 为什么 | 之前 `KNOWN_KEYS` 没列入 `"constraints"`,导致该键被静默路由到 `extras`,`manifest.getConstraints()` 永远返回空 list,下游 B2 pinSkillConstraints 和 agent-4 catalog 锚点全是死代码。 |
| 验证步骤 | 1. `cat test-fixtures/skill-with-constraints/SKILL.md`(如有)确认 frontmatter 有 `constraints: [...]`;2. 运行 `SkillManifestConstraintsParsingTest`。 |
| 预期结果 | `manifest.getConstraints()` 返回非空 list;test 5/5 通过。 |

### 改动 2:ProgressLedgerService 前缀守卫(深挖修复)

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/progress/ProgressLedgerService.java:132-137`

| 项 | 内容 |
|---|---|
| 改了什么 | `upsert()` 入口检查 key 是否以 `auto_` 或 `pin_` 开头,是则抛 `IllegalArgumentException`。 |
| 为什么 | 之前保护是单向的:Java 让位 LLM(auto 不覆盖 LLM 已有 entry),但 LLM 可以用 `progress_update(stepKey="auto_read_file")` 覆盖 Java 写入的条目,导致 auto-recorded 工具记录被改写。 |
| 验证步骤 | 1. `ProgressLedgerPrefixGuardTest.upsertRejectsAutoPrefix`;2. `ProgressLedgerPrefixGuardTest.upsertRejectsPinPrefix`。 |
| 预期结果 | 两个测试均抛 `IllegalArgumentException`;`ProgressLedgerTool` 的 `@Tool` 描述包含前缀保留声明。 |

### 改动 3:upsertAutoRecorded 4 参签名 + 批量化(深挖修复 + 性能优化)

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/progress/ProgressLedgerService.java:227-296`、`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java`(`autoRecordToolCalls`)

| 项 | 内容 |
|---|---|
| 改了什么 | `upsertAutoRecorded` 升级为 4 参签名 `(conversationId, toolName, displayName, resultSummary)`;新增 `upsertAutoRecordedBatch` 批量方法,一次 lock+load+save 处理 N 个工具响应;ActionNode 改为先收集 `List<AutoRecordEntry>` 再一次批量调用。 |
| 为什么 | 1. 跨服务器键碰撞:两个 MCP 服务器都暴露 `search` 工具 → `auto_search` 互相覆盖;2. 并行工具串行化:每个 ToolResponse 单独 lock+load+save 抵消并行收益。 |
| 验证步骤 | 1. `ProgressLedgerPrefixGuardTest.autoRecordedDifferentServersNoCollision`:两个服务器同名工具共存;2. `ProgressLedgerPrefixGuardTest.batchInsertProducesSameResultAsSequential`:批量与逐条结果一致;3. `ProgressLedgerPrefixGuardTest.batchInsertBoundedToMaxFiveEvenWithLargeBatch`:10 条批量插入后有界=5。 |
| 预期结果 | ledger 中同时存在 `auto_mcp_4_search_xxx` 和 `auto_mcp_7_search_yyy`;5 个并行工具调用从 5 次 lock+save 降为 1 次。 |

### 改动 4:B2 pinSkillConstraints——load_skill 后约束写入 pinned

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java`(`pinSkillConstraints`)

| 项 | 内容 |
|---|---|
| 改了什么 | `load_skill` 工具调用成功后,读取 `manifest.getConstraints()`,对每条约束调用 `progressLedgerService.upsertPinned(convId, "pin_<skillName>_<i>", constraintText, note)`。 |
| 为什么 | 把约束从 messages(会被压缩销毁)抽到 DB ledger.pinned(压缩免疫),解决"长对话中 skill 约束丢失"问题。 |
| 验证步骤 | 1. `ContextCompressionLedgerSurvivalTest.loadSkillBodyDestroyedByCompressionButConstraintsSurviveInLedger`;2. `ContextCompressionLedgerSurvivalTest.allThreeLedgerEntryTypesSurviveCompression`。 |
| 预期结果 | 压缩后 messages 中 load_skill 正文消失,但 `ledger.renderSnapshot()` 仍包含 `🔒 固定约束` 段,约束文本字节级保留。 |

### 改动 5:B5 autoRecordToolCalls——工具调用后批量自动记录

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java`(`autoRecordToolCalls`)

| 项 | 内容 |
|---|---|
| 改了什么 | ActionNode 处理 ToolResponse 后,收集所有有效条目到 `List<AutoRecordEntry>`,一次调用 `upsertAutoRecordedBatch`。 |
| 为什么 | 让 LLM 在长对话中即使忘记自己刚调用过什么工具,也能从 ledger 快照看到最近 5 次工具调用记录;批量调用避免 N 次 lock+save 串行化。 |
| 验证步骤 | `ProgressLedgerPrefixGuardTest.autoRecordedBoundedToMaxFive`:模拟 10 次工具调用,验证 auto 条目数等于 5。 |
| 预期结果 | ledger 中 auto 条目始终 ≤ 5,最老的被驱逐;5 个并行工具调用只需 1 次 DB roundtrip。 |

### 改动 6:C4 环境通知注入 nonHistoryPrefix

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java:755-765,1201-1215`

| 项 | 内容 |
|---|---|
| 改了什么 | ReasoningNode 每轮推理前 `registry.drain(conversationId)`,非空则 `renderEnvironmentNotifications` 渲染成 markdown 块,作为 SystemMessage 加入 nonHistoryPrefix。 |
| 为什么 | 让运行时环境变更(MCP 断连 / skill 更新)在下一轮推理立即可见,LLM 主动改路而不是反复重试失效工具。 |
| 验证步骤 | `EnvironmentNotificationRenderingTest.mcpConnectionLostEventEndToEnd_producesActionableLLMText`:注册会话 → 触发 `McpConnectionLostEvent(serverId=7)` → drain → render。 |
| 预期结果 | 渲染块包含 "📢 环境变更通知"、`mcp_7_` 前缀、"不要反复重试" 指令。 |

### 改动 7:A1 PRUNE_EXEMPT_TOOLS 加入 load_skill

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/context/ConversationWindowManager.java:96-120`

| 项 | 内容 |
|---|---|
| 改了什么 | `PRUNE_EXEMPT_TOOLS` 集合从 `{delegateToAgent, delegateParallel}` 扩展为 `{delegateToAgent, delegateParallel, load_skill}`。 |
| 为什么 | `load_skill` 返回的 SKILL.md 是 load-time 快照,skill 作者可能在执行期间更新,重载不保证恢复相同指令;且 50KB+ skill 重载昂贵。 |
| 验证步骤 | `ConversationWindowManagerToolPruningTest`(已有测试套件)。 |
| 预期结果 | load_skill 的 ToolResponseMessage 在 `pruneOldToolResultsForModelInput` / `compactAgedToolResponses` 阶段不被修剪。 |

### 改动 8:agent-2 PrefixedNameToolCallback 描述加 serverName 标签

**文件**:`mateclaw-server/src/main/java/vip/mate/tool/mcp/runtime/PrefixedNameToolCallback.java:55-80`、`mateclaw-server/src/main/java/vip/mate/tool/mcp/runtime/McpClientManager.java:201-300`

| 项 | 内容 |
|---|---|
| 改了什么 | 新增 3 参构造器 `(prefixedName, delegate, serverName)`,serverName 非空时描述前缀 `[MCP server: <name>]`;McpClientManager `wrapServerCallbacks` 透传 serverName。 |
| 为什么 | LLM 看到 `mcp_4_search_a1b2c3` 时无法知道这是哪个服务器的工具;多个 MCP 服务器都暴露 `search` 时,LLM 会混淆。加 `[MCP server: fetch-server]` 标签让 LLM 区分。 |
| 验证步骤 | 启动一个 MCP 服务器,在 agent 工具列表中观察工具描述是否包含 `[MCP server: <name>]` 前缀。 |
| 预期结果 | 每个 MCP 工具描述开头包含 `[MCP server: <serverName>]`;2 参构造器(无 serverName)保持向后兼容,描述不加前缀。 |

### 改动 9:ToolExecutionExecutor 工具不存在时跨服务器候选建议

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/graph/executor/ToolExecutionExecutor.java:1264-1340`

| 项 | 内容 |
|---|---|
| 改了什么 | "Tool not found" 错误信息升级:若请求名是 MCP 格式,搜索 `toolCallbackMap` 中 slug 或 hash6 匹配但 serverId 不同的候选,返回 ≤5 个建议。 |
| 为什么 | LLM 常把 slug 拼到错误 serverId 上重构出不存在工具名,反复重试到 max iterations。给候选建议后 LLM 可以直接复制正确名字。 |
| 验证步骤 | 1. 启动两个 MCP 服务器都暴露 `fetch` 工具;2. 让 LLM 调用 `mcp_<serverA>_fetch_xxx`(实际 fetch 在 serverB);3. 观察错误信息。 |
| 预期结果 | 错误信息包含 "Did you mean one of these?" + 正确的 `mcp_<serverB>_fetch_yyy` 候选名。 |

### 改动 10:Registry TTL 定时清理(防泄漏)

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/runtime/RunningConversationRegistry.java:155-211`

| 项 | 内容 |
|---|---|
| 改了什么 | 新增 `cleanupStale(Duration maxAge)` 方法 + `@Scheduled scheduledCleanup()`(每 5 分钟扫一次,清理 30 分钟未活跃的 handle)。用 `remove(key, value)` 保证不误删被并发 `register` 刷新的 handle。 |
| 为什么 | 兜底防御异常路径泄漏的 handle——即使 `safeUnregister` 因异常路径未执行(如 Reactor cancel 信号不触发 doFinally),后台线程也能回收。 |
| 验证步骤 | `RunningConversationRegistryTest.cleanupStaleRemovesOldHandles`:注册 → 反射 backdate lastActiveAt → 清理 → 验证被移除;`cleanupStaleDoesNotRemoveRefreshedHandle`:backdate 后 re-register → 清理 → 验证存活。 |
| 预期结果 | 30 分钟未活跃的 handle 被清理;被 `register` 刷新的 handle 不被误删。 |

### 改动 11:JSON 格式向后兼容迁移

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/progress/ProgressLedgerService.java:79-85,284-292`

| 项 | 内容 |
|---|---|
| 改了什么 | JSON 从 flat-map `{"step1":{...}}` 升级为 wrapper `{"entries":{...},"pinned":{...}}`;`parseWrapper` 通过 peek `"entries"` 键区分新旧格式,旧格式自动迁移为 wrapper(pinned 为空)。 |
| 为什么 | 老 conversation 的 ledger 列存的是 flat-map,新代码上线后必须能加载老数据。 |
| 验证步骤 | `ContextCompressionLedgerSurvivalTest.oldFlatMapLedgerMigratesToWrapperFormatWithEmptyPinned`:写入旧 JSON → load → 验证 pinned 为空 → upsert → 验证新 JSON 包含 `entries` 和 `pinned` 键。 |
| 预期结果 | 旧 conversation 无需迁移脚本,第一次 load 即兼容;写入时自动转为新格式。 |

## 新增测试验证

**文件**:
- `mateclaw-server/src/test/java/vip/mate/skill/manifest/SkillManifestConstraintsParsingTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/progress/ProgressLedgerPrefixGuardTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/runtime/RunningConversationRegistryTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/context/ContextCompressionLedgerSurvivalTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/graph/node/EnvironmentNotificationRenderingTest.java`

| 命令 | 预期 |
|------|------|
| `mvn -pl mateclaw-server -am test -Dtest='SkillManifestConstraintsParsingTest'` | Tests run: 5, Failures: 0 |
| `mvn -pl mateclaw-server -am test -Dtest='ProgressLedgerPrefixGuardTest'` | Tests run: 22, Failures: 0 |
| `mvn -pl mateclaw-server -am test -Dtest='RunningConversationRegistryTest'` | Tests run: 24, Failures: 0 |
| `mvn -pl mateclaw-server -am test -Dtest='ContextCompressionLedgerSurvivalTest'` | Tests run: 5, Failures: 0 |
| `mvn -pl mateclaw-server -am test -Dtest='EnvironmentNotificationRenderingTest'` | Tests run: 14, Failures: 0 |

## 回归检查清单

- [ ] 全量 `mvn -pl mateclaw-server -am test` 通过(已验证 0 失败 0 错误)
- [ ] 老 conversation(flat-map ledger JSON)首次 load 不报错,pinned 字段为空
- [ ] 多 MCP 服务器场景:LLM 工具列表中每个工具描述包含 `[MCP server: <name>]` 标签
- [ ] MCP 服务器中途断连:agent 下一轮推理看到 `📢 环境变更通知` 块,主动改路
- [ ] 长 conversation(>100 轮)经多次 PTL 压缩后,`ledger.renderSnapshot()` 仍包含 pinned 约束
- [ ] `progress_update(stepKey="auto_xxx")` 被拒绝,返回 `IllegalArgumentException` 错误信息
- [ ] auto-recorded 条目数始终 ≤ 5(10 次工具调用后仍为 5)
- [ ] 5 个并行工具调用只产生 1 次 DB roundtrip(批量 auto-record)
- [ ] Registry 中 30 分钟未活跃的 handle 被后台定时清理
- [ ] MCP/skill 绑定机制(`mate_agent_tool` / `mate_agent_skill` 表)不受影响
- [ ] Plan-Execute 路径(StepExecutionNode)目前**不**接收环境通知——只有 ReAct 路径生效(已知未覆盖项,不阻塞本 PR)

* feat(agent): 六招减法重构——修复压缩销毁 skill 约束与 MCP 按需暴露

## 背景

- 压缩三阶段(softTrim / hardClear / prePruneForSummary)只检查 `isSpillMarker`,不检查 `PRUNE_EXEMPT_TOOLS`,导致 `load_skill` 返回的 SKILL.md 约束、`delegateToAgent` 子智能体转录在压缩中被裁掉,模型在长对话中"忘记"任务规则,根因是"压缩导致注意力失效"。
- skillCatalog 表只列 Skill / Status / Description 三列,bound skill 的 constraints 与 allowedTools 没有任何可见入口,模型加载 skill 后约束仍可能被忽略。
- MCP 工具默认 CORE tier,20+ MCP 工具的 schema 涌入核心列表,挤占 builtin 工具的注意力,且 `DisclosureTier.fromToken(null)` 返回 CORE 导致 `getOrDefault` 的默认值永远不生效。
- 构建期工具过滤分 4 次 pass,重复遍历且无明确 deny/allow 边界。
- skillCatalog 在每次推理步都按当前 loadedSkills 动态渲染,破坏 Anthropic SYSTEM_AND_TOOLS cache 前缀稳定性。
- 进度账本(ProgressLedger)约束条目前缀无保护,跨 MCP server 键碰撞,环境事件无统一路由入口。

## 改动内容

### 文件改动

**主代码(21 个文件)**

- **`mateclaw-server/src/main/java/vip/mate/agent/context/ConversationWindowManager.java`** — Move 4:三阶段新增 `isExemptTool` 检查跳过 `load_skill`/`delegateToAgent`/`delegateParallel`;新增 Phase 2.7 无损 spill evict 在调用 LLM 摘要前把超大工具结果落盘
- **`mateclaw-server/src/main/java/vip/mate/skill/runtime/SkillRuntimeService.java`** — Move 2 & 3:catalog 表新增 Constraints 列(仅 bound skill 显示);新增 `### Bound skill allowed tools` 块
- **`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java`** — Move 1:skillCatalog 用 `render(Set.of())` 静态渲染进 nonHistoryPrefix;loadedThisRun hint 作为 volatile 后缀注入
- **`mateclaw-server/src/main/java/vip/mate/tool/disclosure/DefaultToolDisclosureService.java`** — Move 5:MCP 工具默认 tier 从 CORE 改 EXTENSION;`buildSnapshot` 跳过 null/blank tier 修复 `fromToken(null)→CORE` 陷阱
- **`mateclaw-server/src/main/java/vip/mate/agent/AgentGraphBuilder.java`** — Move 6:构建期权限过滤从 4 次 pass 合并为 2 次(deny 集 + allow 集)
- **`mateclaw-server/src/main/java/vip/mate/agent/AgentService.java`** — 接入 EnvironmentEventRouter 与 RunningConversationRegistry
- **`mateclaw-server/src/main/java/vip/mate/agent/graph/executor/ToolExecutionExecutor.java`** — 工具调用后自动回填 ProgressLedger
- **`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java`** — 渲染 ledger 三段式快照
- **`mateclaw-server/src/main/java/vip/mate/agent/progress/ProgressLedger.java`** — constraints 前缀保护,跨 MCP server 键命名空间隔离
- **`mateclaw-server/src/main/java/vip/mate/agent/progress/ProgressLedgerService.java`** — 写入 constraints 到 pinned 条目
- **`mateclaw-server/src/main/java/vip/mate/skill/manifest/SkillManifest.java`** — 新增 constraints 字段
- **`mateclaw-server/src/main/java/vip/mate/skill/manifest/SkillManifestParser.java`** — 解析 SKILL.md frontmatter 中的 constraints
- **`mateclaw-server/src/main/java/vip/mate/skill/service/SkillService.java`** — skill 更新事件发布
- **`mateclaw-server/src/main/java/vip/mate/tool/builtin/ProgressLedgerTool.java`** — 三段式渲染
- **`mateclaw-server/src/main/java/vip/mate/tool/mcp/runtime/McpClientManager.java`** — MCP 命名透明化
- **`mateclaw-server/src/main/java/vip/mate/tool/mcp/runtime/PrefixedNameToolCallback.java`** — 透明命名映射
- **`mateclaw-server/src/main/java/vip/mate/agent/runtime/EnvironmentEventRouter.java`** — 新增:5 个环境事件监听器
- **`mateclaw-server/src/main/java/vip/mate/agent/runtime/EnvironmentNotification.java`** — 新增:环境通知数据模型
- **`mateclaw-server/src/main/java/vip/mate/agent/runtime/RunningConversationRegistry.java`** — 新增:运行中会话注册表 + TTL 清理
- **`mateclaw-server/src/main/java/vip/mate/skill/event/SkillUpdatedEvent.java`** — 新增:skill 更新事件
- **`mateclaw-server/Dockerfile`** — 构建配置微调

**测试代码(11 个文件)**

- **`ConversationWindowManagerExemptAndSpillTest.java`** — 新增 15 个行为测试,证明 Move 4 生效
- **`SkillRuntimeServiceConstraintsAndToolsTest.java`** — 新增 8 个测试覆盖 Constraints 列与 allowedTools 块
- **`ReasoningNodeLoadedSkillsHintTest.java`** — 新增 8 个测试覆盖 loadedThisRun hint 渲染
- **`CompactionSurvivalComparisonTest.java`** — 新增 4 个场景的新旧代码对比测试(100 轮极限压缩)
- **`ContextCompressionLedgerSurvivalTest.java`** — 压缩后 ledger 存活测试
- **`EnvironmentNotificationRenderingTest.java`** — 环境通知渲染测试
- **`ProgressLedgerPrefixGuardTest.java`** — ledger 前缀保护测试
- **`RunningConversationRegistryTest.java`** — 会话注册表测试
- **`SkillManifestConstraintsParsingTest.java`** — constraints 解析测试
- **`ProgressLedgerStaleReminderTest.java`** — 修复回归
- **`ToolDisclosureServiceTest.java`** — 断言从 CORE 改为 EXTENSION

### 测试

**回归测试**

- `mvn test`(mateclaw-server 全量):**199 通过 / 1 跳过 / 0 失败**

**行为测试(证明改动生效,旧代码上失败)**

- `CompactionSurvivalComparisonTest`(4 个场景):在新代码上全部通过
- 用 `git stash` 还原旧代码后,16 个行为测试编译失败或断言失败 → 证明测试确实覆盖了新行为

**新旧代码对比测试(同一份测试源码,两套代码库运行)**

| 场景 | 旧代码 | 新代码 |
|---|---|---|
| A: 50 load_skill + 50 delegate + 50 read_file 单轮压缩 | load_skill 0/50, delegate 0/50 | **load_skill 50/50, delegate 50/50** |
| B: 100 轮极限压缩 + 头部 pinned load_skill | root_constraint_survived=**false**, 113ms | root_constraint_survived=**true**, 60ms |
| C: 20 个不同大小 load_skill 单轮压缩 | 0/20 存活, tokens 8694→754 | **20/20 存活**, tokens 8694→8694 |
| D: 30 轮稳态压缩 + pinned skill | pinned_survived=**false** | pinned_survived=**true** |

### 安全性

- `DisclosureTier.fromToken(null)` 陷阱修复:旧代码 `serverTierById.put(id, CORE)` 导致 `getOrDefault` 默认值永不生效;新代码跳过 null tier,未配置的 MCP server 才走 EXTENSION 默认值
- `PRUNE_EXEMPT_TOOLS` 保护范围从 2 处扩展到 5 处,避免 `load_skill` 约束被压缩销毁后模型在无约束下执行敏感操作

## 逐项验证

### 改动 1:nonHistoryPrefix 分层稳定化

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java:701-714, 776-788, 1246-1257`

| 项 | 内容 |
|---|---|
| 改了什么 | skillCatalog 用 `render(Set.of())` 静态渲染进 nonHistoryPrefix;loadedThisRun hint 作为 volatile 后缀注入 |
| 为什么 | 每次推理步都按 loadedSkills 动态渲染会破坏 Anthropic SYSTEM_AND_TOOLS cache 前缀,导致 cache 失效增加 token 成本 |
| 验证步骤 | 1. 打开 ReasoningNode.java:701;2. 确认 `skillCatalogRenderer.render(java.util.Set.of())` 调用;3. 跑 `ReasoningNodeLoadedSkillsHintTest` |
| 预期结果 | 8 个测试通过,loadedThisRun hint 作为后缀注入,不破坏前缀缓存 |

### 改动 2:skillCatalog 增加 Constraints 列

**文件**:`mateclaw-server/src/main/java/vip/mate/skill/runtime/SkillRuntimeService.java:502-561, 634-641`

| 项 | 内容 |
|---|---|
| 改了什么 | catalog 表从 3 列扩为 4 列,新增 Constraints 列(仅 bound skill 显示,长约束截断,pipe 转义);新增 `### Bound skill allowed tools` 块 |
| 为什么 | bound skill 的 constraints 没有任何可见入口,模型加载后仍可能忽略 |
| 验证步骤 | 1. 跑 `SkillRuntimeServiceConstraintsAndToolsTest`;2. 检查 catalog 渲染包含 Constraints 列 |
| 预期结果 | 8 个测试通过,bound skill 显示 constraints,非 bound skill 省略 |
- **边界验证**:长约束截断为单行;pipe 字符被转义不破坏表格

### 改动 3:修复 PRUNE_EXEMPT_TOOLS 在三阶段的绕过

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/context/ConversationWindowManager.java:990-994, 1030-1090, 1160-1210`

| 项 | 内容 |
|---|---|
| 改了什么 | `softTrimToolResults`、`hardClearToolResults`、`prePruneForSummary` 三处新增 `isExemptTool` 检查,跳过 `load_skill`/`delegateToAgent`/`delegateParallel` |
| 为什么 | 旧代码只在 `pruneOldToolResultsForModelInput` 和 `compactAgedToolResponses` 检查 exempt,三阶段不检查,导致 skill 约束在压缩中被裁掉 |
| 验证步骤 | 1. 跑 `ConversationWindowManagerExemptAndSpillTest`;2. 跑 `CompactionSurvivalComparisonTest` |
| 预期结果 | 15 个行为测试通过;100 轮压缩后 load_skill body 存活率 100% |
- **反例对照**:在新代码上跑对比测试,旧代码存活率 0%,新代码 100%

### 改动 4:Phase 2.7 无损 spill evict

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/context/ConversationWindowManager.java:440-468, 1263-1300`

| 项 | 内容 |
|---|---|
| 改了什么 | 在 Phase 2 hardClear 之后、LLM 摘要之前新增 Phase 2.7,把超大工具结果落盘替换为 spill marker |
| 为什么 | 旧代码超出预算直接走 LLM 摘要(有损+耗时+费 token),其实大部分场景落盘就够 |
| 验证步骤 | 1. 检查 `spillEvictToolResults` 方法;2. 跑 `ConversationWindowManagerExemptAndSpillTest.spillEvictReducesTokenCount` |
| 预期结果 | spill 后 token 数低于预算时跳过 LLM 摘要,strategy=lossless_spill_evict |

### 改动 5:MCP 工具默认 EXTENSION

**文件**:`mateclaw-server/src/main/java/vip/mate/tool/disclosure/DefaultToolDisclosureService.java:78-105, 276-336`

| 项 | 内容 |
|---|---|
| 改了什么 | `resolveTierByName` 默认返回 EXTENSION;`buildSnapshot` 跳过 null/blank tier 的 server 不放入 map |
| 为什么 | MCP schema 是 prompt 最重部分,默认 CORE 挤占 builtin 工具注意力;`fromToken(null)` 返回 CORE 导致默认值失效 |
| 验证步骤 | 1. 跑 `ToolDisclosureServiceTest.mcpDefaultsExtensionWhenServerTierUnset`;2. 检查未配置 tier 的 MCP server 工具不在 active 列表 |
| 预期结果 | 未配置 tier 的 MCP 工具进入 extensionCatalog,需 `enable_tool` 激活 |
- **边界验证**:显式 `disclosure_tier=core` 的 server 仍保持 CORE

### 改动 6:构建期权限过滤合并

**文件**:`mateclaw-server/src/main/java/vip/mate/agent/AgentGraphBuilder.java:258-310`

| 项 | 内容 |
|---|---|
| 改了什么 | 4 次 pass 合并为 2 次:先 `withDeniedToolsFiltered(deniedSet)`,再 `withAllowedToolsOnly(boundTools)` |
| 为什么 | 重复遍历浪费构建时间,且 deny/allow 边界不清晰 |
| 验证步骤 | 1. 检查 AgentGraphBuilder.java:258-310;2. 跑全量回归测试确认工具过滤行为不变 |
| 预期结果 | 工具列表与改动前一致,构建步骤减少 |

## 新增测试验证

**文件**:

- `mateclaw-server/src/test/java/vip/mate/agent/context/ConversationWindowManagerExemptAndSpillTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/context/CompactionSurvivalComparisonTest.java`
- `mateclaw-server/src/test/java/vip/mate/skill/runtime/SkillRuntimeServiceConstraintsAndToolsTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/graph/node/ReasoningNodeLoadedSkillsHintTest.java`
- `mateclaw-server/src/test/java/vip/mate/skill/manifest/SkillManifestConstraintsParsingTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/progress/ProgressLedgerPrefixGuardTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/runtime/RunningConversationRegistryTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/graph/node/EnvironmentNotificationRenderingTest.java`
- `mateclaw-server/src/test/java/vip/mate/agent/context/ContextCompressionLedgerSurvivalTest.java`

| 命令 | 预期 |
|------|------|
| `mvn -Dtest=ConversationWindowManagerExemptAndSpillTest test` | 15 个测试通过 |
| `mvn -Dtest=CompactionSurvivalComparisonTest test` | 4 个场景通过,新代码 load_skill 存活率 100% |
| `mvn -Dtest=SkillRuntimeServiceConstraintsAndToolsTest test` | 8 个测试通过 |
| `mvn -Dtest=ReasoningNodeLoadedSkillsHintTest test` | 8 个测试通过 |
| `mvn test`(全量) | 199 通过 / 1 跳过 / 0 失败 |

**新旧对比测试运行命令**:

```bash
# 新代码
cd /data/mateclaw/mateclaw-server && mvn -Dtest=CompactionSurvivalComparisonTest -Dsurefire.useFile=false test

# 旧代码(需把测试复制到 mateclaw-old)
cd /data/mateclaw/mateclaw-old/mateclaw-server && mvn -Dtest=CompactionSurvivalComparisonTest -Dsurefire.useFile=false test
```

## 回归检查清单

- [ ] `mvn test` 全量通过(199/1skip/0fail)
- [ ] 对比测试在新代码上 load_skill 存活率 100%
- [ ] 对比测试在旧代码上 load_skill 存活率 0%(证明测试有效)
- [ ] MCP 工具默认进入 extensionCatalog,`enable_tool` 可激活
- [ ] 显式 `disclosure_tier=core` 的 MCP server 仍保持 CORE
- [ ] 100 轮压缩后 root_constraint 仍存活
- [ ] Phase 2.7 spill evict 在预算内时跳过 LLM 摘要
- [ ] skillCatalog 静态渲染不依赖 loadedSkills,前缀缓存稳定
2026-07-06 11:50:41 +08:00
.github/ISSUE_TEMPLATE sync: settings UI polish, channel reliability fixes, DeepSeek cross-turn fix 2026-04-29 11:22:47 +08:00
assets docs(readme): surface 1.3.0 themes in README + architecture diagrams 2026-05-14 15:10:03 +08:00
docker/searxng fix(docker): bake searxng settings.yml into custom image 2026-04-24 23:25:03 +08:00
docs feat(plugin): 插件化搜索 Provider — PluginType.SEARCH + PluginSearchProvider SPI (#477) (#479) 2026-07-03 16:57:27 +08:00
mateclaw-desktop chore: bump version to 1.8.0-SNAPSHOT 2026-07-06 11:40:52 +08:00
mateclaw-plugin-api feat(plugin): 插件化搜索 Provider — PluginType.SEARCH + PluginSearchProvider SPI (#477) (#479) 2026-07-03 16:57:27 +08:00
mateclaw-plugin-sample chore(build): centralize Maven revision management 2026-05-18 10:01:11 +08:00
mateclaw-plugin-search-sample feat(plugin): 插件化搜索 Provider — PluginType.SEARCH + PluginSearchProvider SPI (#477) (#479) 2026-07-03 16:57:27 +08:00
mateclaw-server feat(agent): 注意力锚定与环境感知——MCP 工具溯源 + skill 约束固定 + 事件通知 (#490) 2026-07-06 11:50:41 +08:00
mateclaw-ui chore: bump version to 1.8.0-SNAPSHOT 2026-07-06 11:40:52 +08:00
mateclaw-webchat fix(webchat): align demo and widget theme tokens 2026-05-04 19:23:45 +08:00
rfcs feat(kb-open): Deep Research 开放 API(start/SSE/status/cancel) (#446) 2026-07-02 17:47:24 +08:00
.dockerignore chore: bump version to 1.1.137-SNAPSHOT 2026-04-18 21:58:54 +08:00
.env.example feat(browser): 放开内网服务访问限制,新增局域网部署模式开关 (#472) 2026-07-02 09:25:16 +08:00
.gitignore fix(mcp): fail-closed on unknown channel + signing-key self-heal (#471) 2026-07-02 11:13:27 +08:00
docker-compose.yml feat(browser): 放开内网服务访问限制,新增局域网部署模式开关 (#472) 2026-07-02 09:25:16 +08:00
LICENSE chore: add Apache-2.0 license 2026-04-04 23:29:51 +08:00
pom.xml chore: bump version to 1.8.0-SNAPSHOT 2026-07-06 11:40:52 +08:00
README_zh.md release: v1.7.0 2026-07-04 20:28:15 +08:00
README.md release: v1.7.0 2026-07-04 20:28:15 +08:00

MateClaw Logo

MateClaw

Your second brain

Agent Harness · Spring Boot inside · One JAR to ship

GitHub Repo Documentation Live Demo Website Java Version Spring Boot Vue Last Commit License

[Website] [Live Demo] [Documentation] [中文]

MateClaw Preview


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.

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

Surface What it is
Web Console Full admin — digital employees, models, skills, knowledge, security, cron, runtime console (see what every employee is doing, force-recycle in one click)
Desktop Electron app with a bundled JRE 21. Double-click, run. No Java install
Webchat Widget One <script> tag embed. Drop it on any site
IM Channels DingTalk · Feishu · WeChat Work · WeChat · Telegram · Discord · QQ · Slack
Plugin SDK Java module for third-party capability packs

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

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


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 memoryAGENTS.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

MateClaw OpenClaw Hermes Agent Claude Code Cursor
Multi-vendor failover Chain + health tracker + cooldown Swap providers via config Orchestration w/ retry Anthropic only One model
Knowledge digestion LLM Wiki + page-level citations Canvas + memory Skills Hub + memory Code index
Multi-user admin RBAC + approval + audit + runtime console Config-file first Single-user CLI Enterprise tier Teams plan
Capability extension Skills (LESSONS) + MCP + ACP MCP MCP
Surfaces Web admin + Desktop + Widget + SDK + 8 IM 25+ chat channels 15+ channels (CLI-led) 3 IM preview IDE only
Stack Java (Spring Boot) TypeScript Python TypeScript Electron/TS
License / Price Apache 2.0 · Free MIT · Free MIT · Free Proprietary · $20200/mo Proprietary · $0200/mo

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.


Quick start

# 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

Docker

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

Desktop

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


Architecture

Business Architecture

Technical architecture

Technical Architecture


Project structure

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.

Tech stack

Layer Technology
Backend Spring Boot 3.5 · Spring AI Alibaba 1.1 · MyBatis Plus · Flyway
Digital Employee Runtime StateGraph · ReAct + Plan-Execute · Role / Goal / Backstory · LESSONS self-evolution
Orchestration Workflow (7 step modes · Pebble DSL) · Triggers (6 pattern types · event governance) · Wiki Transformations (1.3.0+)
Capability Extension SKILL.md packages · MCP (stdio / SSE / HTTP · per-agent binding) · ACP bridge (Claude Code / Codex)
Database H2 (dev) · MySQL 8.0+ (prod)
Auth Spring Security + JWT
Frontend Vue 3 · TypeScript · Vite · Element Plus · TailwindCSS 4
Desktop Electron · electron-updater · JRE 21 (bundled)
Widget Vite library mode · UMD + ES bundles

Documentation

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

Roadmap

v1.7.0 (shipped 2026-07-04) — a productionization pass: once it's in real collaboration, close every loop you can't see, gather, reach, fit, or connect:

  • All three approval paths close the loop — workflow await_approval actually pushes to channels and resolves → resumes, the WebChat (API-key) channel can approve/deny and replay, and Feishu/WeCom card clicks resolve workflow approvals directly
  • Long tasks are visible — an always-on Run Overview rail + a per-turn token breakdown (cache hit/miss/write + reasoning split) + sub-agent cost rolled up + one-click generated-file download
  • Fits the real model window — local-model context-window probing, a unified token budget for prefix injection, small-context degradation, and tool-schema budget gating — no more "guess 32K" pre-flight rejections or silent truncation
  • Opens up — a knowledge-base + Deep Research open API (API-key + rate limit + SSE), a pluggable search Provider SPI, and MCP identity forwarding (carry the authenticated user's identity into a STDIO MCP)
  • Reaches further — desktop local-embedded / remote-centralized dual mode (with mateclaw-desktop source opened) + a LAN deployment mode for controlled intranet access
  • One-click operational data export — Dashboard 9-sheet Excel + a CLI for offline export

Full story in the v1.7.0 release notes.

v1.6.0 (shipped 2026-06-22) — make the autonomous employee fast, sharp-eyed, and embeddable: two-stage skill loading + prefix compression (faster first token) · execute_code native sandboxed code execution · vision that persists across turns + image_analyze · embeddable/headless webchat with per-endUserId memory · a Wiki you actually read (reading split from management · unified Sources tab · clickable [[wikilinks]]) · steadier under load (self-healing MCP · tool-call recovery · evidence-gated plans). Full story in the v1.6.0 release notes.

v1.5.0 (shipped 2026-06-04) — Goal checklists (fuzzy score → ticked boxes) · self-maintaining Wiki ([[wikilinks]] · fact/experience layers · pageType profiles & permissions · KB pipelines · local-directory ingest) · per-owner memory isolation (owner_key + visibility scope + endUserId passthrough) · per-agent primary knowledge base · provider-preference model routing. Full story in the v1.5.0 release notes.

v1.4.0 (shipped 2026-05-23) — Persistent Goals (lock a goal, self-evaluate every turn) · subagent delegation tree (3 levels deep · sync / parallel / async · one-sentence team builder) · progressive tool/skill disclosure · Workspace RBAC (Owner / Admin / Member / Viewer) · Feishu first-class (interactive / approval / streaming cards · channel-native tools). See the v1.4.0 release notes.

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.

Contributing

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

Why the name

Mate is companion. Claw is capability.

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

License

Apache License 2.0. No asterisks.