Ami Survey

Name: Ami Survey
Author: speedofred

by speedofredversion 1.2.0i★ –iRuns on your computer

Registry nameio.github.speedofred/ami-survey

Install

Overview

Description from the maker (original English)

Measures the cost, tokens and duration of a completed agent workflow from its session log.

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 checksi1 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: Other
You need to fill in: AMI_API_TOKEN

Install

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

Before you install

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

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx 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": {
    "ami-survey": {
      "command": "uvx",
      "args": [
        "ami-survey"
      ],
      "env": {
        "AMI_API_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ami-survey --env AMI_API_TOKEN=your-value -- uvx ami-survey

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": {
    "ami-survey": {
      "command": "uvx",
      "args": [
        "ami-survey"
      ],
      "env": {
        "AMI_API_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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ami-survey": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ami-survey"
      ],
      "env": {
        "AMI_API_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.

Values you fill in

AMI_API_TOKEN secret env
An existing AMI submission token. Optional: if unset, the client registers this machine on first use and stores the token locally.

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

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account speedofred, which owns the repo
… 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 Otheri

More stars than 0% of the other 32708 servers in this category
Published to the registry more recently than 38% of the other 32708 servers in this category
Basic checks equal to or better than 100% of the other 32708 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 Ami Survey safe?

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.

What keys or codes does it need?

You need to fill in: AMI_API_TOKEN

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 (1.2.0) 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 Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, OpenTakeoff

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

Spec Driven Development

by formulahendry

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

Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

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

Runs in the cloud★ 211Updated 2 days ago

Install

OpenTakeoff

by Kentucky-ai

Construction takeoff for AI agents: load plans, set scale, measure, count, export with provenance.

Runs on your computerUpdated today

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.

AMI survey client

Measures what a completed agent workflow cost to run, by reading the runtime's own session log, and submits the result to the AMI survey at survey.agentbenchmark.dev.

The cost of a single API call is easy to obtain. The cost of one finished piece of work is not: one triaged ticket, one screened CV, one drafted reply, across every call, retry and tool round-trip the agent made getting there. This measures that figure.

Every number is read from the runtime's records rather than reported by the agent. An agent asked how many tokens it has just used will estimate, and will present the estimate with confidence.

What comes back

A real run of six support tickets, triaged and answered by Claude Opus 5 in Claude Code:

Maturity Index      85.0  Strong          (observability 40%, evidence 30%, quality 30%)

Performance 78.13 Strong confidence Very High

quality 80.0 graded Good on ami-quality-v2 cost 72.73 $0.123226 per ticket ($0.739355 for the run) speed 84.47 20.90s per ticket evidence 70.0 measured, on a self-issued token observability 100.0

findings weakness Cost is the weakest pillar at 72.73; speed is strongest at 84.47. $0.123226 per unit against a $0.01 reference. A cheaper model, or fewer calls, moves this; check calls[] for where the tokens went.

note Cost and speed were scored against a provisional reference, which is a placeholder rather than a measurement. Do not quote them as settled yet. The Maturity Index does not use the reference and is unaffected.

$0.12 per ticket, 21 seconds per ticket. That is the figure this exists to produce, and it is the one most teams cannot currently state about their own work.

The findings record where the scorecard's own numbers are soft. A cost reference that is still a placeholder is reported as a placeholder rather than folded into the score.

Install

There are two routes. What separates them, and what separates the hosts below, is whether anything can read your runtime's logs. That determines whether the result is recorded as measured or unmeasured.

Install the client

One block of configuration, then restart the agent.

Claude Code, in ~/.claude.json, or through the Developer settings in Claude Desktop:

{ "mcpServers": { "ami-survey": { "command": "uvx", "args": ["ami-survey"] } } }

Runs are measured: the client reads Claude Code's own session log, so the token counts and the cost come from the runtime rather than from the agent.

Codex (measured)

In ~/.codex/config.toml. Codex uses TOML here, not JSON:

[mcp_servers.ami-survey]

command = "uvx" args = ["ami-survey"]

The client reads Codex's rollout log. This also covers a local or self-hosted model driven through Codex, because the log is written either way.

Copilot (not measured)

In .vscode/mcp.json, or your user profile through the MCP: Open User Configuration command. The key is servers here, not mcpServers:

{ "servers": { "ami-survey": { "command": "uvx", "args": ["ami-survey"] } } }

The tools work and the survey submits, but Copilot writes no session log the client can read. The run carries the workflow, the grade and the stage timings without token counts or cost, and is recorded as unmeasured.

Then, once the agent finishes a piece of work, ask it:

Take the AMI survey regarding the ticket triage you just did

There is nothing to clone and nothing to keep updated. No token needs to be supplied: the first call that requires one registers the machine and stores the token at ~/.ami-survey/token.

uvx is part of uv, the tool the MCP documentation uses for Python servers. If uv is not installed, GETTING-STARTED.md gives a pipx form and a route that requires neither.

If you already hold a token, set it as AMI_API_TOKEN in that block's env and it will be used instead of registering a new one.

Or use the remote connector, with nothing installed

In claude.ai, open Settings, then Connectors, then Add custom connector, and supply:

https://survey.agentbenchmark.dev/mcp

Nothing is installed and no token is required. These runs are recorded as unmeasured and are never compared against measured ones: a remote server cannot read your runtime's logs, so token counts and cost are absent rather than estimated.

Licence

MIT. Use it, modify it, redistribute it, include it in your own work.

The licence covers this client only. It grants no rights in the survey service the client submits to, or in the data that service collects.

Full terms in LICENSE.

What leaves your computer

Token counts, timings, model names, the stage names the workflow declared, and the grade. Not your files, not your prompts, not your shell commands. GETTING-STARTED.md sets this out in full.

Submissions go to survey.agentbenchmark.dev and nowhere else. That destination is a constant in the source rather than a setting, so a stale environment variable cannot redirect a submission onto your own disk. That is the one failure which would make a run appear successful while collecting nothing.

Requirements

Python 3.9 or newer. No dependencies; the standard library only.

Ami Survey

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 Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

OpenTakeoff

README from the maker

AMI survey client

What comes back

Install

Install the client

Or use the remote connector, with nothing installed

Licence

What leaves your computer

Requirements

Further reading