Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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.
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。
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。
选择你使用的 AI 应用,然后复制设置。
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
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。
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。
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。
NATS_TRAIL_API env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。
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
注册名称已通过 GitHub 账户 solsolettidev 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
你需要填写:NATS_TRAIL_TOKEN
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)。
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。
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。
同一分类中有:Spec Driven Development, Remote Desktop Commander, First Sale Scout
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Playbooks and a 14-day checklist for founders winning their first paying customers.
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.
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:
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 Trail | Typical NATS MCP server | |
|---|---|---|
| Tool schemas | Explicit JSON input and output schemas per tool | None, or input only |
| Result size | limit is required, capped at 200, with cursors | Unbounded |
| Long scans | maxScan budget with explicit truncation warnings | Scans until it dies |
| Message shape | subject, timestamp, stream/seq, truncation flag, extracted request_id / correlation_id | Raw payload dump |
| Errors | Structured envelope with code and retriable | Stack traces or plain strings |
| Writes | Unreachable from the agent runtime | publish, KV and object writes exposed |
| Audit | Every call logged with origin and token identity; mutations with their arguments | None |
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.
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
/api and /ws to the bridge)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).
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
natstrail.search_messages natstrail.get_message_detail natstrail.trace_by_request_id natstrail.trace_by_correlation_id natstrail.search_dlq natstrail.run_filter
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
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.
┌── 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.
nats-trail binary: query commands, serve, and an interactive shell.See docs/architecture.md.
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.
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.
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
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