47 AI models as MCP tools: LLM, image, video, audio, embeddings & more. x402 or API key.
Most AI and media services work still happens through a UI a human drives. Gpu MCP server moves it into the conversation instead. 47 AI models as MCP tools: LLM, image, video, audio, embeddings & more. x402 or API key.
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.
The server publishes 7 tools. What each one is for:
gpu_run — Run any GPU-Bridge service. The primary tool for executing AI tasksgpu_catalog — Get the full catalog of available services with pricing and capabilitiesgpu_estimate — Estimate cost before running a service. No authentication requiredgpu_status — The gpu_status tool exposed by this servergpu_balance — Check your current balance, daily spend, and volume discount tierVideo — The Video tool exposed by this serverUtilities — The Utilities tool exposed by this serverConfiguration is passed through the environment: GPUBRIDGE_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Gpu's toolset — gpu_run, gpu_catalog, gpu_estimate and 4 more — is a fair guide to whether it matches your workflow. It is maintained by fjnunezp75; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| gpu_run | Run any GPU-Bridge service. The primary tool for executing AI tasks. |
| 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 | The gpu_status tool exposed by this server. |
| gpu_balance | Check your current balance, daily spend, and volume discount tier. |
| Video | The Video tool exposed by this server. |
| Utilities | The Utilities tool exposed by this server. |
{
"mcpServers": {
"gpu-bridge": {
"command": "npx",
"args": ["-y", "@gpu-bridge/mcp-server"],
"env": {
"GPUBRIDGE_API_KEY": "your_api_key_here"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| GPUBRIDGE_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.