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getnahook/nahook-mcp

getnahook/nahook-mcp

Nahook webhook platform: trigger
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add nahook-mcp -- npx -y nahook-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
1 ★ · getnahook/nahook-mcp · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 1 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 getnahook/nahook-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

nahook-mcp

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

The official **Model Context Protocol** server for Nahook — drive webhook deliveries, endpoints, and event triggers from Claude Desktop, Cursor, Cline, and any other MCP-compatible AI assistant.
> The MCP server ships as a subcommand of the nahook CLI. One binary, one credentials file, one install path.
What it does
Once installed and authenticated, your AI assistant can:
- **Inspect** endpoints, deliveries, and per-attempt logs to debug failed webhooks.
- **Retry** failed or dead-lettered deliveries.
- **Trigger** events and fan them out to every subscribed endpoint.
- **Send** webhooks directly to a single endpoint.
- **Manage** endpoints (create, update, pause, resume) — never delete, by design.
Write operations are tagged with the MCP destructiveHint/readOnlyHint annotations so MCP clients surface a per-call human-approval prompt before anything mutates state.
Security guardrails
Webhook payloads are third-party data, so the server treats everything that flows back into the model's context as a potential prompt-injection channel:
- **Untrusted content is fenced.** Every producer- or receiver-authored value that reaches the model — webhook payloads (get_delivery with include_payload), delivery idempotency keys, and receiver error messages (list_attempts) — is wrapped in explicit >> delimiters with embedded fence markers neutralized, and the server instructions tell the model to treat fenced content as inert data, never as instructions.
- **Payloads are capped.** Bodies over 256 KB are truncated (flagged via payload_truncated) so a hostile producer can't stuff the model's context. Tune the cap with NAHOOK_MCP_PAYLOAD_CAP= in the MCP client's environment.
- **No delete tools, by design.** Nothing in the tool surface can destroy data.
- **update_endpoint is marked destructive.** It overwrites live endpoint config (repointing its URL is the primitive an injection would target), so its destructiveHint is true and clients surface a prominent approval prompt.
- **Write tools rely on human approval.** Per the MCP spec, annotations are advisory hints, not access control — the security boundary is the client's per-call approval prompt, which applies to every non-read tool. The additive write tools (create_endpoint, send_to_endpoint, trigger_event) are annotated destructiveHint: false per their spec semantics; keep human-in-the-loop approval enabled in your MCP client and don't blanket-allow them. If you want a hard guarantee of no writes, run the server without an ingestion key (disables sending) and treat management tools as approval-gated.
- **Secrets never reach the model.** Endpoint signing secrets and auth tokens are omitted from every tool output; whoami returns only the token's public id.
- **Split credentials.** Sending (trigger_event, send_to_endpoint) requires a separate ingestion key — omit it and the server is management/read-only for ingestion.
Client-side measures can't make prompt injection impossible — pair them with your MCP client's tool-approval prompts.
Install
The MCP server is a subcommand of the nahook CLI. Install the CLI, then add it to your AI client.
来源
awesome · https://github.com/getnahook/nahook-mcp
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