gpu-bridge-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GPUBRIDGE_API_KEY | No | Your GPU-Bridge API key from gpubridge.io. Optional if using the x402 protocol for keyless agent payments. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| gpu_runA | Run any GPU-Bridge AI service. 30 services available: LLM inference (sub-second), image generation (FLUX, SD3.5), video generation, video enhancement (up to 4K), speech-to-text (Whisper, <1s), TTS (40+ voices), music generation, voice cloning, embeddings, document reranking (Jina), OCR, PDF/document parsing, NSFW detection, image captioning, visual Q&A, background removal, face restoration, upscaling, stickers, and more. Use gpu_catalog to see all available services. |
| gpu_catalogA | List all available GPU-Bridge services with pricing and model info. No authentication required. |
| gpu_statusB | Check the status of a GPU-Bridge job and retrieve results. |
| gpu_balanceA | Check GPU-Bridge credit balance, daily spend, volume discount tier, and job history. |
| gpu_estimateA | Estimate the cost of a GPU-Bridge service before running it. No authentication required. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no overlap: balance checking, catalog listing, cost estimation, job execution, and status monitoring. The descriptions make it unambiguous which tool to use for each task, preventing misselection.
All tools follow a consistent 'gpu_' prefix with descriptive suffixes (balance, catalog, estimate, run, status). This verb_noun pattern is uniform throughout, making the tool set predictable and easy to navigate.
With 5 tools, this server is well-scoped for its GPU service management purpose. Each tool earns its place by covering essential operations: account management, service discovery, cost estimation, job execution, and status tracking, without being overly sparse or bloated.
The tool set provides complete coverage for the GPU service lifecycle: discover services (catalog), estimate costs, run jobs, monitor status, and manage account (balance). No obvious gaps exist; agents can perform end-to-end workflows without dead ends.