Skip to main content
Glama

cueapi-mcp

CueAPI 的官方 Model Context Protocol 服务器,CueAPI 是 AI 代理系统的开源协调层。

让您支持 MCP 的助手(Claude Desktop、Cursor、Zed 或任何其他 MCP 主机)能够在对话中调度代理工作、获取执行历史记录,并使用基于证据的结果报告来闭环。

为什么

代理无法通过一次调用完成任务。它们需要在时间、工具、环境、代理和人类之间进行协调。每一次交接都是隐藏静默失败的地方。CueAPI 通过结构化证据(外部 ID、结果 URL 或工件)来结束每一次交接。此 MCP 服务器为代理提供了对该表面的直接访问,因此代理既可以调度自己的后续工作,也可以提供带有证明的结果报告。

Related MCP server: moo-tasks

安装

npm install -g @cueapi/mcp
# or use via npx (no install):
npx -y @cueapi/mcp

配置 (Claude Desktop)

将其添加到您的 Claude Desktop 配置中(macOS 上为 ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "cueapi": {
      "command": "npx",
      "args": ["-y", "@cueapi/mcp"],
      "env": {
        "CUEAPI_API_KEY": "cue_sk_..."
      }
    }
  }
}

在 cueapi.ai 生成您的 API 密钥。自托管?请设置 CUEAPI_BASE_URL 以及 CUEAPI_API_KEY。

配置 (Cursor / Zed / 其他主机)

任何支持 stdio 服务器的 MCP 主机都可以运行此程序。将主机指向 cueapi-mcp 二进制文件,并在环境中传递 CUEAPI_API_KEY。

公开的工具

工具

功能

cueapi_create_cue

创建循环 (cron) 或一次性 (at) 提示

cueapi_list_cues

列出提示,按状态过滤

cueapi_get_cue

获取单个提示的详细信息

cueapi_fire_cue

立即触发现有提示,可选负载覆盖

cueapi_update_cue

更新提示的可变字段(名称、调度、回调、负载等)

cueapi_pause_cue

暂停提示,使其停止触发

cueapi_resume_cue

恢复已暂停的提示

cueapi_delete_cue

永久删除提示

cueapi_list_executions

列出历史执行记录,按提示/状态过滤

cueapi_get_execution

通过 ID 获取单个执行记录,包含状态 + 结果

cueapi_list_claimable_executions

列出可领取的执行记录,按任务/代理在服务器端过滤

cueapi_claim_execution

原子化领取特定执行记录以进行处理

cueapi_claim_next_execution

领取下一个可用执行记录(可选任务过滤器)

cueapi_execution_heartbeat

延长正在进行的执行记录的领取租约

cueapi_report_outcome

报告带有证据(外部 ID / URL)的一次性结果

对话示例

您: 安排一个每天上午 9 点的工作,将摘要发布到我的 webhook。

助手(使用 cueapi_create_cue): 已创建提示 cue_abc123,首次触发时间为明天 UTC 时间 9:00。

您: 向我展示它最后五次的运行记录。

助手(使用 cueapi_list_executions): ...

开发

npm install
npm test        # vitest smoke tests for the tool surface
npm run build   # compile TypeScript to dist/
npm run dev     # run the server locally with tsx

链接

更新日志

  • 0.4.1. 添加 cueapi_update_cue 工具:更新提示的可变字段(名称、调度、回调 URL、时区、负载、描述)。封装 PATCH /v1/cues/{id}。稀疏更新 — 仅发送提供的字段。弥补了跨包装器的对等差距(其他所有客户端包装器都公开了更新;MCP 之前没有)。

  • 0.4.0. 添加五个执行生命周期工具 — cueapi_get_execution、cueapi_list_claimable_executions、cueapi_claim_execution、cueapi_claim_next_execution、cueapi_execution_heartbeat。为希望在会话内(例如 Claude Desktop、Cursor、Zed)使用工作者传输执行记录的 MCP 主机代理关闭了接收-领取-处理-完成循环。亮点:list_claimable_executions 通过 task / agent 查询参数在服务器端进行过滤(客户端过滤会遇到已知的 LIMIT-50 饥饿错误);claim_next_execution 接受可选的 task_name 并在内部进行扇出(过滤列表 → 选择最旧的 → 按 ID 领取),因为服务器尚不支持在原始领取端点上进行任务过滤;execution_heartbeat 通过 X-Worker-Id 请求头发送 worker_id(服务器用于该字段的传输),并要求在模式中包含它,以便配置错误的调用者在包装器处失败,而不是静默绕过竞争保护。内部:CueAPIClient.request() 获得了一个可选的 extraHeaders 参数,以支持每次调用的自定义标头。

  • 0.3.0. 添加 cueapi_fire_cue 工具:使用可选的 payload_override(以及 merge_strategy: 'merge' | 'replace',默认为 'merge')立即触发现有提示。封装 POST /v1/cues/{id}/fire。让代理无需创建一次性提示即可触发临时执行,并让每次触发的动态数据流向 webhook 分发 + 工作者领取响应,而无需更改存储的提示。

  • 0.1.4. 修复 cueapi_pause_cue / cueapi_resume_cue 以使用 PATCH /v1/cues/{id} 和 {"status": "paused" | "active"}(之前调用了不存在的 /pause 和 /resume 端点,返回运行时 404)。PR #1。这是实际包含修复的版本;0.1.3 在发布时带有此说明,但未合并代码。

  • 0.1.3. 过早发布,被 0.1.4 取代。与 0.1.2 相比没有功能变化。

  • 0.1.2. 在官方 MCP 注册表中注册。

  • 0.1.0. 初始版本:8 个用于创建/列出/获取/暂停/恢复/删除提示、列出执行记录、报告结果的工具。

许可证

MIT © Vector Apps Inc.

Available Tools

8 tools
cueapi_create_cueA

Create a new CueAPI cue — a scheduled job that fires a callback (or enqueues worker work) on a cron or one-time trigger.

Inputs: name (required), cron, at, callback_url, +4 more.

cueapi_delete_cueA

Delete a cue permanently. Irreversible.

Inputs: cue_id (required).

cueapi_get_cueA

Fetch a single cue by ID, including current schedule and most recent execution.

Inputs: cue_id (required).

cueapi_list_cuesC

List cues on the authenticated account, optionally filtered by status.

Inputs: status, limit, offset.

cueapi_list_executionsB

List executions — the historical record of times a cue actually fired. Optionally filter by cue, status, or paginate.

Inputs: cue_id, status, limit, offset.

cueapi_pause_cueA

Pause a cue. Paused cues do not fire until resumed.

Inputs: cue_id (required).

cueapi_report_outcomeA

Report the outcome of an execution. CueAPI's core accountability primitive: attach evidence (external_id, result_url, summary) that proves the work actually happened. Write-once — the outcome record is immutable.

Inputs: execution_id (required), success (required), external_id, result_url, +1 more.

cueapi_resume_cueB

Resume a previously-paused cue.

Inputs: cue_id (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.8/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose targeting specific operations on cues or executions. There is no overlap: create, delete, get, list, pause, resume, list_executions, and report_outcome are all unique actions with well-defined boundaries.

    Naming Consistency5/5

    All tools follow a consistent 'cueapi_verb_noun' pattern with snake_case throughout. The naming is predictable and uniform, making it easy to understand each tool's function at a glance.

    Tool Count5/5

    With 8 tools, the server is well-scoped for managing cues and executions. Each tool earns its place, covering core CRUD operations, lifecycle management (pause/resume), and accountability features without being overwhelming.

    Completeness5/5

    The toolset provides complete coverage for the CueAPI domain: full CRUD for cues (create, get, list, delete), lifecycle control (pause/resume), execution tracking (list_executions), and accountability (report_outcome). There are no obvious gaps, enabling agents to handle all typical workflows.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
      214
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server for agentic task orchestration and management, enabling AI agents to create goals, plan tasks with acceptance criteria, track dependencies, request human input, and provide proof of completion.
      16 npm
      3
      MIT
    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables enterprise agent fleets to register workers, dispatch tasks by capability, monitor continuous heartbeat telemetry, trip automated circuit breakers, and recover from checkpointed state through a zero-dependency MCP server.
      MIT