Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
GPU cloud platform — create, manage, and monitor instances, snapshots, SSH keys, and billing.
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.
You need
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Works in Claude on the web, desktop and mobile:
https://api.thundercompute.com:8443/mcpRun this in your terminal
claude mcp add --transport http thunder-compute https://api.thundercompute.com:8443/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"thunder-compute": {
"url": "https://api.thundercompute.com:8443/mcp"
}
}
}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": {
"thunder-compute": {
"type": "http",
"url": "https://api.thundercompute.com:8443/mcp"
}
}
}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.
ChatGPT connects only to servers on the internet:
https://api.thundercompute.com:8443/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
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 6, 2026
The registry name was verified with the GitHub account Thunder-Compute, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, dotnet-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.
MCP server for .NET symbols, XAML, source generators, and restricted workspace edit
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tnr is the official command-line interface for Thunder Compute, a high-performance cloud GPU platform built for AI/ML prototyping and experimentation. Using a proprietary orchestration engine, Thunder Compute delivers fast provisioning, low-latency execution, and low-cost GPU compute designed for developer workflows.
The tnr CLI supports:
Install tnr using one of the supported methods below. You may also download installers and binaries directly from the Latest Release page.
Download the .pkg installer for your platform from the Latest Release page (tnr_*_darwin_arm64.pkg for Apple Silicon, tnr_*_darwin_amd64.pkg for Intel).
Homebrew:
brew tap Thunder-Compute/tnr
brew install tnr
Download .tar.gz, .deb, .rpm, or .apk packages from the Latest Release page.
Install script (recommended):
curl -fsSL https://raw.githubusercontent.com/Thunder-Compute/thunder-cli/main/scripts/install.sh | bash
Download the .msi installer for your platform from the Latest Release page.
Scoop:
scoop bucket add tnr https://github.com/Thunder-Compute/scoop-bucket
scoop install tnr
Winget:
winget install Thunder.tnr
git clone https://github.com/Thunder-Compute/thunder-cli.git
cd thunder-cli go build -o tnr ./tnr
tnr login # Authenticate with Thunder Compute
tnr create # Create a GPU instance tnr status # View instance status tnr connect 0 # Connect to your instance
tnr scp myfile.py 0:/home/ubuntu/ tnr scp 0:/home/ubuntu/results.txt ./
tnr delete 0 # Delete instance
tnr login opens a browser and returns to a loopback callback on 127.0.0.1. On a headless or remote machine where that callback cannot be reached, create a named API token in Console Settings and run tnr login --token instead.
Run tnr report for a guided report in the style of tnr create: choose Report a problem or Suggest an improvement, write a one-sentence summary and the details, then review the report and choose Send report, Edit report, or Cancel. Sign in before starting. --kind, --subject, and --details or --details-file fill in their steps, which are then skipped, and supplied text is sent as given. Quitting sends nothing and exits with code 130. Noninteractive reports default to bugs; use --kind feedback for product feedback.
tnr report --subject "Upload connection drops" --details-file ./report.txt --component cli --instance 42
tnr report --kind feedback --subject "Show remaining disk space" --details "Please show disk usage in the instance list." --yes --json tnr report --subject "Unexpected result" --details-file - --dry-run --json < ./report.txt
Noninteractive submission requires --subject, --details or --details-file, and --yes. --json never prompts. --details-file - reads standard input. --details and --details-file are mutually exclusive. Subject and details limits are 200 and 10,000 Unicode characters; oversized text is rejected instead of truncated. --dry-run previews without authentication or submission and identifies the missing server-resolved requester.
Optional context flags are --component (cli, console, api, mcp, virtualization, or unknown), either --instance or --sandbox, and --occurred-at (RFC 3339). The report includes the CLI version, build commit and date, OS, and architecture. The server records submission time and resolves the requester from your login or verified API token owner. No logs, environment variables, shell history, or workload files are collected automatically. Only include evidence you intend to share with support, and omit credentials.
Successful submissions print an opaque report reference. Exit zero means a successful submission or dry run. Any failure exits nonzero and retains the entered report in the error output, so you can submit it again. JSON errors include error, message, and report. Reporting skips automatic update and subscription checks.
This project is licensed under the MIT License. See LICENSE for details.