Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Read-only NATS and JetStream observability: trace a request across streams, rank what is broken.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
NATS_TRAIL_API, NATS_TRAIL_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
}
}
}
}Run this in your terminal
claude mcp add nats-trail --env NATS_TRAIL_API=your-value --env NATS_TRAIL_TOKEN=your-value -- npx -y @nats-trail/mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"nats-trail": {
"command": "npx",
"args": [
"-y",
"@nats-trail/mcp"
],
"env": {
"NATS_TRAIL_API": "your-value",
"NATS_TRAIL_TOKEN": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"nats-trail": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@nats-trail/mcp"
],
"env": {
"NATS_TRAIL_API": "your-value",
"NATS_TRAIL_TOKEN": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
NATS_TRAIL_API envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account solsolettidev, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: NATS_TRAIL_TOKEN
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.6.1) reached the registry 35 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Aiterm MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Persistent terminals and one launcher for Claude, Codex, Grok, Cursor, and Antigravity harnesses.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
Only the beginning is shown; read the rest in the repo