Gpu Bridge

Name: Gpu Bridge
Author: gpu-bridge

by gpu-bridgeversion 2.4.3i★ –iRuns on your computer

Registry nameio.github.fjnunezp75/gpu-bridge

Install

Overview

Description from the maker (original English)

30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more.

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: Design, images & audio
You need to fill in: GPUBRIDGE_API_KEY

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: GPUBRIDGE_API_KEY

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

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": {
    "gpu-bridge": {
      "command": "npx",
      "args": [
        "-y",
        "@gpu-bridge/mcp-server"
      ],
      "env": {
        "GPUBRIDGE_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add gpu-bridge --env GPUBRIDGE_API_KEY=your-value -- npx -y @gpu-bridge/mcp-server

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": {
    "gpu-bridge": {
      "command": "npx",
      "args": [
        "-y",
        "@gpu-bridge/mcp-server"
      ],
      "env": {
        "GPUBRIDGE_API_KEY": "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": {
    "gpu-bridge": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@gpu-bridge/mcp-server"
      ],
      "env": {
        "GPUBRIDGE_API_KEY": "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

GPUBRIDGE_API_KEY secret env
GPU-Bridge API key (get one at https://gpubridge.io). Starts with gpub_. Optional if using x402 micropayments.

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 (fjnunezp75) is not the repo owner (gpu-bridge); 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 Design, images & audioi

More stars than 0% of the other 2186 servers in this category
Published to the registry more recently than 3% of the other 2186 servers in this category
Basic checks equal to or better than 35% of the other 2186 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 Gpu Bridge 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?

You need to fill in: GPUBRIDGE_API_KEY

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 (2.4.3) reached the registry 8 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: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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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.

GPU-Bridge MCP Server

30 GPU-powered AI services as MCP tools — LLMs, image generation, audio, video, embeddings, reranking, PDF parsing, NSFW detection & more.

x402 native for autonomous AI agents: pay per request on-chain with USDC on Base L2. No API keys. No accounts.

What is GPU-Bridge?

GPU-Bridge is a unified GPU inference API with native x402 support — the open payment protocol that allows AI agents to autonomously pay for compute with USDC on Base L2. No API keys, no accounts, no human intervention required.

This MCP server exposes all 30 GPU-Bridge services as Model Context Protocol tools, giving Claude (and any MCP-compatible AI) direct access to GPU inference.

Install in Claude Desktop (2 minutes)

1. Get your API key (or use x402 for autonomous agents)

Visit gpubridge.io and grab a free API key, or use the x402 protocol for keyless agent payments.

2. Add to `claude_desktop_config.json`

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

"mcpServers": { "gpu-bridge": { "command": "npx", "args": ["-y", "@gpu-bridge/mcp-server"], "env": { "GPUBRIDGE_API_KEY": "your_api_key_here" } } } }

3. Restart Claude Desktop

That's it. Claude now has access to 30 GPU-powered AI services.

MCP Tools

`gpu_run`

Run any GPU-Bridge service. The primary tool for executing AI tasks.

Parameters:

service (string) — Service key (e.g., "llm-4090", "flux-schnell", "whisper-l4") input (object) — Service-specific input parameters priority (string) — Optional: "fast" (lowest latency) or "cheap" (lowest cost)

`gpu_catalog`

Get the full catalog of available services with pricing and capabilities.

`gpu_estimate`

Estimate cost before running a service. No authentication required.

`gpu_status`

Check the status of a job and retrieve results.

`gpu_balance`

Check your current balance, daily spend, and volume discount tier.

30 Available Services

Language Models (LLMs)

Service ID	Description	Notes
`llm-4090`	General purpose LLM	Sub-second via Groq
`llm-a100`	Maximum capability LLM	Largest models
`llm-l4`	Ultra-fast, low cost LLM	Budget option
`code-4090`	Code generation	Optimized for code
`llm-stream`	Streaming LLM responses	Real-time output

Image Generation

Service ID	Description	Notes
`flux-schnell`	FLUX.1 Schnell	Fast, 4-step generation
`flux-dev`	FLUX.1 Dev	High quality
`sdxl-4090`	Stable Diffusion XL	Versatile
`sd35-l4`	Stable Diffusion 3.5	Latest SD model
`img2img-4090`	Image-to-image	Style transfer, editing

Vision & Image Analysis

Service ID	Description	Notes
`llava-4090`	Visual Q&A	Image understanding
`ocr-l4`	Text extraction (OCR)	Multi-language
`rembg-l4`	Background removal	Instant
`caption-4090`	Image captioning	Auto-describe images
`nsfw-detect`	Content moderation	NSFW classification

Speech-to-Text

Service ID	Description	Notes
`whisper-l4`	Fast transcription	Sub-second
`whisper-a100`	High accuracy transcription	Large files
`diarize-l4`	Speaker diarization	Who said what

Text-to-Speech

Service ID	Description	Notes
`tts-l4`	Voice cloning TTS	40+ voices
`tts-fast`	Ultra-fast TTS	Lowest latency
`bark-4090`	Expressive TTS	Emotion, laughter

Audio Generation

Service ID	Description	Notes
`musicgen-l4`	Music generation	Text-to-music
`audiogen-l4`	Sound effects	Text-to-SFX

Embeddings & Search

Service ID	Description	Notes
`embed-l4`	Text embeddings	Multilingual
`embed-code`	Code embeddings	For code search
`rerank`	Document reranking	Jina, sub-second

Video

Service ID	Description	Notes
`animatediff`	Text-to-video	AnimateDiff
`video-enhance`	Video upscaling	Up to 4K

Utilities

Service ID	Description	Notes
`pdf-parse`	Document parsing	PDF/DOCX to text

x402: For Autonomous AI Agents

GPU-Bridge supports the x402 payment protocol, enabling truly autonomous AI agents to pay for compute without human intervention.

Agent Request → GPU-Bridge returns HTTP 402 Payment Required

↓ Agent pays USDC on Base L2 (gas < $0.01, settles in 2s) ↓ Agent retries with payment proof → GPU-Bridge executes and returns result

Python Example with x402

from x402.client import PaymentClient

client = PaymentClient(private_key="0x...", chain="base")

response = client.request( "POST", "https://api.gpubridge.io/v1/run", json={ "service": "flux-schnell", "input": {"prompt": "A robot painting on a canvas", "steps": 4} } ) print(response.json())

Pricing

Category	Starting From
LLMs	$0.003/1K tokens
Image Generation	$0.01/image
Speech-to-Text	$0.005/minute
Text-to-Speech	$0.005/1K chars
Embeddings	$0.0001/1K tokens
Reranking	$0.001/query
PDF Parsing	$0.005/document

All prices in USD. x402 payments in USDC on Base L2.

Gpu Bridge

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 Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

GPU-Bridge MCP Server

What is GPU-Bridge?

Install in Claude Desktop (2 minutes)

1. Get your API key (or use x402 for autonomous agents)

2. Add to claude_desktop_config.json

3. Restart Claude Desktop

MCP Tools

gpu_run

gpu_catalog

gpu_estimate

gpu_status

gpu_balance

30 Available Services

Language Models (LLMs)

Image Generation

Vision & Image Analysis

Speech-to-Text

Text-to-Speech

Audio Generation

Embeddings & Search

Video

Utilities

x402: For Autonomous AI Agents

Python Example with x402

Pricing

Links

License

2. Add to `claude_desktop_config.json`

`gpu_run`

`gpu_catalog`

`gpu_estimate`

`gpu_status`

`gpu_balance`