Trail

Name: Trail
Author: arsprengel

by arsprengelversion 1.29.1i★ –iRuns on your computer

Registry namedev.usetrail/trail

Install

Overview

Description from the maker (original English)

Issue tracker and durable project memory for your coding agent, scoped to the folder you open.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi0 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 0 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: TRAIL_API_URL, TRAIL_PROJECT

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "trail": {
      "command": "npx",
      "args": [
        "-y",
        "usetrail"
      ],
      "env": {
        "TRAIL_API_URL": "your-value",
        "TRAIL_PROJECT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add trail --env TRAIL_API_URL=your-value --env TRAIL_PROJECT=your-value -- npx -y usetrail

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "trail": {
      "command": "npx",
      "args": [
        "-y",
        "usetrail"
      ],
      "env": {
        "TRAIL_API_URL": "your-value",
        "TRAIL_PROJECT": "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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "trail": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "usetrail"
      ],
      "env": {
        "TRAIL_API_URL": "your-value",
        "TRAIL_PROJECT": "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.

Values you fill in

TRAIL_API_URL env
Only for a self-hosted Trail. Left unset, the connector points at the hosted service.
TRAIL_PROJECT env
Overrides the project name, which otherwise comes from the folder you have open.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

! Caution
Maker matches the repo
The publisher (usetrail.dev) is not the repo owner (arsprengel); someone else may have listed it
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7250 servers in this category
Published to the registry more recently than 44% of the other 7250 servers in this category
Basic checks equal to or better than 33% of the other 7250 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Trail safe?

It passed 0 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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.29.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

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.

usetrail

The MCP server for [Trail](https://usetrail.dev) - it gives your coding agent your team's tracker and the project's durable memory, scoped to the folder you have open.

Your agent stops working blind. It reads what is open, writes what it did, and records what it learned the hard way - in the same board your team looks at, not in a scratch file that only that session can see.

This package is the client. It talks to your Trail account over the REST API; there is no database here. Dependencies are @modelcontextprotocol/sdk, zod and the built-in fetch.

Quick start

# 1. connect this machine to your Trail account (opens your browser; no token to copy)

npx -y usetrail@latest login

2. register it with your agent - this example is Claude Code

claude mcp add trail -s user -- npx -y usetrail@latest

No account yet? Create one at usetrail.dev - the free plan covers three projects and three people.

Not tied to one agent. This is a plain MCP server over stdio, speaking the three protocol versions in use today. Any MCP-compatible client can run it; only the registration command differs, and each client documents its own.

Prefer a local checkout? Clone it instead, and the connector keeps itself up to date on its own (see Updating):

git clone https://github.com/arsprengel/trail-mcp.git ~/.trail-mcp

npm --prefix ~/.trail-mcp install --omit=dev node ~/.trail-mcp/bin.js login claude mcp add trail -s user -- node ~/.trail-mcp/bin.js

On Windows, write the real path instead of ~: the registration stores the argument verbatim and Node does not expand it.

What your agent gets

The tracker - list_items, get_item, add_item, update_item, move_item, get_next, delete_item. Real items on your team's board, with type, status, priority, assignees and history. Work the agent picks up shows as in progress and closes when it is done, so the board is not a story someone has to retell.

Project memory - list_memory, get_memory, add_memory, update_memory, review_memory. The durable knowledge of a project: the deploy that has a trap in it, the decision nobody should relitigate, the command that is not in any README. Shared by everyone on the project, human or agent. A new session reads it before acting instead of rediscovering it.

Reminders - add_reminder, list_reminders, update_reminder, delete_reminder. Things with a date that must not be silently missed - and the agent closes or reschedules them itself once the date arrives.

Attachments - add_attachment, get_attachment. Files that belong to an item.

Which project it writes to

Trail holds many projects. The connector uses the folder you have open as the project - the folder name, or whatever a .trail file next to it says, or the TRAIL_PROJECT variable. So the agent writes to the right project without being told, and two repositories never bleed into each other. To reach across, the agent passes project explicitly on the tool.

Session hook (Claude Code, Gemini CLI, Antigravity)

Installed for you, once, when you log in - and on the connector's first run, which covers people who paste a token into the registration instead of logging in through the browser. Every session that starts in a project with a tracker gets the open items and the project memory in context from the first message - the agent starts knowing, instead of depending on someone remembering to ask. Fail-silent by design: no login or no network and the hook stays quiet.

Each tool keeps this in its own place, so the connector writes to the one that tool actually reads:

Claude Code - a session-start hook in ~/.claude/settings.json.
Gemini CLI - a session-start hook in ~/.gemini/settings.json.
Antigravity - the tools are registered in ~/.gemini/config/mcp_config.json, which is the file it actually reads: `gemini mcp add` does not connect Trail in Antigravity, because that command writes to ~/.gemini/settings.json instead. Field-tested on Antigravity 2.11 (Windows), of the three things that live in that config folder only the tool registration is honored - the opening-summary hook is not run, and a plugin folder placed exactly where its own documentation says is not read. So on Antigravity the agent gets the tools and the server's working rules, and fetches the project summary itself on the first turn instead of receiving it. The plugin path is built and tested behind a switch, waiting for that to change.

usetrail status tells you, per tool found on this machine, whether it is on - so you never have to go digging through settings files to find out.

It never fights you. A tool that isn't on the machine gets nothing created for it, and hooks install will not fabricate a config for a program you don't have. If you remove it with hooks uninstall, it does not come back on its own - put it back with:

npx -y usetrail@latest hooks install

Clients without a hook mechanism are covered too: the server's own instructions tell the agent to fetch the summary itself before acting.

Your own Trail

Point it at your server once and it stays pointed:

TRAIL_API_URL=https://your-trail npx -y usetrail@latest login

Without that variable, login goes to the hosted service.

Commands

npx -y usetrail@latest            # start the MCP server over stdio - what your agent runs

npx -y usetrail@latest login # connect this machine (browser confirmation, no token copying) npx -y usetrail@latest status # server address, current project, whether a token is present npx -y usetrail@latest logout # delete the saved token npx -y usetrail@latest doctor # find the install on this machine and unstick auto-updates

The token is stored at ~/.config/trail/token.json (mode 600). Revoke it whenever you want from the "AI token" panel in the app.

Configuration

Variable	What it does
`TRAIL_API_URL`	Your own Trail's address. Saved after the first login. Defaults to the hosted service.
`TRAIL_PROJECT`	Forces the project name (default: the open folder).
`TRAIL_API_TOKEN`	A token directly, skipping the browser login. Useful in CI.
`TRAIL_LANG`	Language of what the connector prints on screen: `pt` or `en`. Without it, your system's language, and English when your system states none. Never changes what the agent reads.

The former names (TETHER_*) keep working, with no deadline - the product used to be called Tether, and nothing anyone already configured has to change.

Updating

The `@latest` is not decoration. Registered as npx -y usetrail@latest, the connector resolves the published version every time your agent starts a session, so a new release reaches you without anyone doing anything. Registered as bare npx usetrail, npm reuses whatever copy it cached the first time - and that machine stays on that version forever. Use @latest.

The cost of @latest is about a second at session start, and a network call. Neither matters in practice: the connector talks to Trail over the network anyway.

A cloned install updates itself differently: on startup it fires a quiet fast-forward pull in the background, at most every six hours. The running session keeps the version it loaded; the next one starts updated. No network or a local conflict and nothing happens, silently.

Stuck on an old version? npx -y usetrail@latest doctor finds the install, reports the version and unsticks it.

Requirements

Node 18 or newer.

License

MIT. This package is the client - the connector you run on your own machine. Use it, fork it, adapt it. The Trail service it talks to is a separate, hosted product.

Trail

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

usetrail

Quick start

2. register it with your agent - this example is Claude Code

What your agent gets

Which project it writes to

Session hook (Claude Code, Gemini CLI, Antigravity)

Your own Trail

Commands

Configuration

Updating

Requirements

License