原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Nats Trail

作者:solsolettidev版本 0.6.1i★ –i在你的电脑上运行
注册名称io.github.solsolettidev/nats-trail

安装

概览

作者提供的说明(英文原文)

Read-only NATS and JetStream observability: trace a request across streams, rank what is broken.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:NATS_TRAIL_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: NATS_TRAIL_API, NATS_TRAIL_TOKEN

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "nats-trail": {
      "command": "npx",
      "args": [
        "-y",
        "@nats-trail/mcp"
      ],
      "env": {
        "NATS_TRAIL_API": "your-value",
        "NATS_TRAIL_TOKEN": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add nats-trail --env NATS_TRAIL_API=your-value --env NATS_TRAIL_TOKEN=your-value -- npx -y @nats-trail/mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "nats-trail": {
      "command": "npx",
      "args": [
        "-y",
        "@nats-trail/mcp"
      ],
      "env": {
        "NATS_TRAIL_API": "your-value",
        "NATS_TRAIL_TOKEN": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "nats-trail": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@nats-trail/mcp"
      ],
      "env": {
        "NATS_TRAIL_API": "your-value",
        "NATS_TRAIL_TOKEN": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • NATS_TRAIL_API env
    URL of the NATS Trail bridge, e.g. http://127.0.0.1:4000. Without it the server answers only from local state and cannot reach JetStream.
  • NATS_TRAIL_TOKEN 机密 env
    Bearer token for the bridge, required when it has auth enabled. A read-scoped token is enough: this server never mutates.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 solsolettidev 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32715 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32715 个服务器的 53% 更新
  • 基础检查结果等于或优于此分类中其他 32715 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Nats Trail 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:NATS_TRAIL_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.6.1)于35天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, First Sale Scout

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

First Sale Scout

作者:firstsale.pro

Playbooks and a 14-day checklist for founders winning their first paying customers.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Give an AI agent safe access to your production event bus.

A web UI, a CLI and an MCP server over one bounded query engine — so humans and agents debug NATS from the same source of truth.


Why this exists

Every NATS GUI answers *"what is in this stream?"*. That is the easy question.

The hard question in an event-driven system is "why did this one flow fail?" — and answering it means following a single request_id across four streams, three services and a dead-letter subject. Today you do that by hand, with a terminal per stream.

NATS Trail answers that question directly, and exposes the answer to agents as a typed, bounded, read-only tool contract — so you can point Claude at production and ask.

nats-trail trace --request-id req-0001d --limit 20

Or, from an agent: *"Why did the refresh for s3-events fail?"* — and it lands on the message that actually broke, with the retry state and the correlation ids already extracted:


The part nobody else does

There are several NATS MCP servers. They shell out to the nats CLI, return raw dumps, and expose publish and delete while describing themselves as read-only.

NATS Trail treats the agent surface as a contract, not a wrapper:

NATS TrailTypical NATS MCP server
Tool schemasExplicit JSON input and output schemas per toolNone, or input only
Result sizelimit is required, capped at 200, with cursorsUnbounded
Long scansmaxScan budget with explicit truncation warningsScans until it dies
Message shapesubject, timestamp, stream/seq, truncation flag, extracted request_id / correlation_idRaw payload dump
ErrorsStructured envelope with code and retriableStack traces or plain strings
WritesUnreachable from the agent runtimepublish, KV and object writes exposed
AuditEvery call logged with origin and token identity; mutations with their argumentsNone
"Read-only" here means unreachable, not disabled

NATS Trail *can* write: publish, purge, delete messages, consumers and streams. Those live behind /api/mutate, reachable from the UI and the CLI.

executeMcpTool() receives an McpRuntimeData interface that exposes only read functions. There is no disabled publish behind a feature flag — there is no `publish` to call. A misconfigured environment variable cannot purge your production stream, because the code path does not exist. CLI write commands additionally refuse to run under --agent, and the test suite reads the source to assert none of this has been quietly undone.

This is the only reason it is reasonable to hand an agent a prod context.


Install

npx nats-trail serve

Open http://127.0.0.1:4000 — one process serves the UI and the API.

Prefer containers? The compose file brings up NATS Trail next to a JetStream-enabled server:

docker compose up

On Kubernetes, the Helm chart declares contexts and correlation keys in values.yaml and keeps credentials in a Secret:

helm install nats-trail ./charts/nats-trail -f my-values.yaml

See charts/nats-trail/README.md for declarative config, why it is a single-replica StatefulSet, and how authentication is delegated to whatever fronts the service.

From source

git clone https://github.com/solsolettidev/nats-trail

cd nats-trail npm install npm start

Development with hot reload

npm run dev
  • UI: http://localhost:5173 (proxies /api and /ws to the bridge)
  • API bridge: http://localhost:4000

npm run dev runs the TypeScript watcher, the API bridge and the UI together.

Requirements: Node.js >= 22 (for the built-in SQLite used by the correlation index) and a reachable NATS server (nats-server -js is fine).


Use it as an MCP server

Point any MCP client at the stdio server. For Claude Code:

claude mcp add nats-trail -- npx -y @nats-trail/mcp

Or wire it manually:

{

"mcpServers": { "nats-trail": { "command": "natstrail-mcp", "env": { "NATS_TRAIL_API": "http://127.0.0.1:4000", "NATS_TRAIL_TOKEN": " " } } } }

Twenty-five read-only tools, all returning the same envelope:

# start here when the topology is unknown

natstrail.discover_subjects subjects that carry traffic + inferred payload shapes natstrail.get_health_summary what is broken right now, ranked natstrail.reconstruct_flow the causal chain for one request_id natstrail.enrich_incident flat context for an incident: flow + dead letters + health

messages

natstrail.search_messages natstrail.get_message_detail natstrail.trace_by_request_id natstrail.trace_by_correlation_id natstrail.search_dlq natstrail.run_filter

topology

natstrail.list_streams natstrail.get_stream_info natstrail.list_consumers natstrail.list_kv_buckets natstrail.list_kv_keys natstrail.get_kv_history natstrail.list_object_buckets natstrail.list_objects

operations

natstrail.get_server_health natstrail.list_server_connections natstrail.list_contexts natstrail.get_connection_status natstrail.list_filters natstrail.list_audit natstrail.enrich_sentry

See docs/mcp-agent.md.


Three surfaces, one engine

                 ┌──  Web UI          explore visually, save filters

Query Engine ───┼── CLI scripts, pipelines, humans in a terminal (core) └── MCP + HTTP API agents, Sentry, dashboards

A filter you save in the UI is the same filter nats-trail filter run executes, and the same one natstrail.run_filter hands an agent. Configure a context once; use it everywhere.

  • `packages/ui` — React + Vite. Presentation only.
  • `packages/server` — Express + WebSocket bridge. Owns connections and credentials.
  • `packages/core` — the Query Engine: envelopes, limits, truncation, filters, error normalization.
  • `packages/cli` — the nats-trail binary: query commands, serve, and an interactive shell.
  • `packages/mcp` — tool contracts and the stdio server.

See docs/architecture.md.


Features

Inspect — context selector (local / dev / staging / prod) with a prod confirmation gate, live subject subscription, JSON pretty print with tree view and in-payload search, stream and consumer browsing, auto-detected DLQ panel.

JetStream — streams, subjects, counts and consumer health. and a selected message rendered as a JSON tree"> NATS Core — live subject subscription with filters.

DLQ — auto-detected dead letters with reason and origin.

Viewer — tree, raw, search, fullscreen, copy-path.

Understand — subject discovery infers payload shapes from real traffic, flow reconstruction turns one request_id into a causal chain, and the health summary ranks what is actually broken.

Query — bounded stream scans with cursors and time windows, filters by subject, date, text and JSON event type, saved filters shared across all three surfaces. Binary payloads (protobuf, msgpack) are detected and shown as hex dumps rather than mojibake.

Browse — KV buckets with per-key revision history including deletes, Object Store metadata, and server health from the monitoring port (varz / jsz / connz).

Change — publish, request/reply, purge, and delete messages, consumers and streams, from the UI and the CLI, behind confirmation. Never from the agent surface.

Integrate — read-only HTTP API under /api/integration, bearer tokens with per-token audit identity, and POST /api/integration/enrich/sentry to attach NATS context to an error without exposing credentials.

Full list in docs/features.md · CLI reference in docs/cli.md.


Security

Credentials live in contexts stored locally under data/ (git-ignored). The UI never holds the NATS connection — it always goes through the bridge, which pools one connection per context.

The server binds to 127.0.0.1 by default because /api/contexts and /api/connect are unauthenticated local endpoints. To expose the Integration API and the WebSocket, configure bearer tokens with NATS_TRAIL_TOKENS=name:token or data/tokens.json; audit entries then record the authenticated token name per call.

A shared deployment has no built-in login on purpose: identity comes from whatever fronts the service (an ingress with OIDC, oauth2-proxy, Cloudflare Access, Teleport or network isolation), so no passwords are stored here. Contexts declared through NATS_TRAIL_CONFIG resolve ${VAR} from the environment and cannot be edited or deleted through the API.


Roadmap

Tracked in docs/roadmap.md.

Phases 0–3 are complete. npm release · KV and Object Store browsing · server health · binary payload handling · nkey auth · subject discovery · flow reconstruction · health summary · incident enrichment for Sentry, Grafana, Datadog and PagerDuty · stream, consumer and KV administration · MCP registry listing · indexed correlation search · declarative config and a Helm chart. All writes are human-only, behind scoped tokens and audited with their arguments.

Next: cluster awareness, deliberately deferred rather than pending work.

Deliberately out — protobuf and msgpack *field* decoding (needs a per-subject schema registry) and competing with NUI on GUI breadth. See docs/roadmap.md.

Planned, not started: for teams that explicitly want agent wri

只显示了开头部分;其余内容请在仓库中阅读

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