Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y @gpu-bridge/[email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
GPUBRIDGE_API_KEY=<secret> claude mcp add io.github.fjnunezp75-gpu-bridge -- npx -y @gpu-bridge/mcp-server@2.4.3รันในเทอร์มินัล
{ "mcpServers": { "io.github.fjnunezp75-gpu-bridge": { "command": "npx", "args": [ "-y", "@gpu-bridge/[email protected]" ], "env": { "GPUBRIDGE_API_KEY": "<secret>" } } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
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.
30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more.
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.
Visit gpubridge.io and grab a free API key, or use the x402 protocol for keyless agent payments.
claude_desktop_config.jsonmacOS: ~/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"
}
}
}
}
That's it. Claude now has access to 30 GPU-powered AI services.
gpu_runRun 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_catalogGet the full catalog of available services with pricing and capabilities.
gpu_estimateEstimate cost before running a service. No authentication required.
gpu_statusCheck the status of a job and retrieve results.
gpu_balanceCheck your current balance, daily spend, and volume discount tier.
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
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())
All prices in USD. x402 payments in USDC on Base L2.
MIT © Healthtech Capital LLC
30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more.
{ "mcpServers": { "io.github.fjnunezp75-gpu-bridge": { "command": "npx", "args": [ "-y", "@gpu-bridge/[email protected]" ], "env": { "GPUBRIDGE_API_KEY": "<secret>" } } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ผู้เผยแพร่ระบุตัวแปรสภาพแวดล้อมเหล่านี้: GPUBRIDGE_API_KEY
Gpu Bridge ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-09 30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more.