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VAP Media · Unified MCP Server for AI Agents (Flux · Veo · Suno)

VAP Media · Unified MCP Server for AI Agents (Flux · Veo · Suno)

Generate AI images, videos, and music with deterministic pricing. MCP Badge MCP Registry Version Python License Get Started


Get Started

No setup required – start generating in 2 minutes:

  1. Create Agent → Get your API key instantly

  2. Add Funds → Start from $1

  3. Generate → Start creating images, videos, and music


Why VAP?

VAP is an MCP server that enables image, video, and music generation directly from agentic workflows. It exposes generative media capabilities as portable, pay-per-use tools usable across Claude Desktop, Cursor, and other MCP-compatible clients.

When AI agents work with paid APIs, they need:

  • Cost visibility – Know exactly what you'll pay before execution

  • Retry control – Bounded, predictable retry behavior

  • Clear ownership – Every task tracked and accountable

  • Enterprise auth – OAuth 2.1 M2M for secure integrations

VAP provides this control layer.


What VAP Does

VAP is an MCP Server that provides Flux image generation, Veo 3.1 video generation, and Suno V5 music generation with full cost control.

Supported AI Models:

  • Flux2 Pro – Photorealistic images

  • Veo 3.1 – Cinematic videos

  • Suno V5 – Original music

Production Pipeline:

  • FFmpeg post-processing (format conversion, audio normalization)

  • Automatic quality optimization for broadcast standards

  • Permanent cloud storage with instant CDN delivery

How it works:

  • Pre-commit pricing – Know exact cost before execution

  • Reserve → Burn → Refund – Hard budget guarantees

  • Deterministic behavior – Predictable results every time

  • Explicit ownership – Every task has a clear owner


How It Works

Agent: "Generate an image of a sunset" ↓ VAP: "Reserving cost..." VAP: "Reserved. Executing..." VAP: "Success. Here's your image."

If it fails:

Agent: "Generate an image of a sunset" ↓ VAP: "Reserving cost..." VAP: "Reserved. Executing..." VAP: "Failed. Full refund. Error: Provider timeout"

Your agent never sees the complexity. It just gets deterministic results.


Presets

Type

Preset

Image

image.basic

Video

video.basic

Music

music.basic

Campaign+SEO

streaming_campaign

Full Production+SEO

full_production

All media productions are automatically normalized and delivered through a fast, orchestrated pipeline in accordance with defined broadcast quality standards.

Pricing: See vapagent.com for current pricing.


MCP Integration

Step 1: Get Your API Key

Option A: Dashboard (Recommended)

Go to vapagent.com/dashboard/signup.html and create your agent.

Option B: API

curl -X POST https://api.vapagent.com/v3/agents \ -H "Content-Type: application/json" \ -d '{"name": "my-agent"}'

Save the api_key from the response. It's shown only once.

Step 2: Activate Your Account

Deposit minimum $1 to unlock generation capabilities:

curl -X POST https://api.vapagent.com/v3/deposits/init \ -H "Authorization: Bearer YOUR_API_KEY" \ -d '{"amount": 5.00, "provider": "crypto"}'

Step 3: Configure Your MCP Client

Claude Desktop

Add to claude_desktop_config.json:

{ "mcpServers": { "vap": { "url": "https://api.vapagent.com/mcp", "transport": "streamable-http", "headers": { "Authorization": "Bearer YOUR_API_KEY" } } } }

Cursor

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{ "mcpServers": { "vap": { "command": "npx", "args": [ "mcp-remote", "https://api.vapagent.com/mcp", "--header", "Authorization: Bearer YOUR_API_KEY" ] } } }

Cline (VS Code)

Add to Cline MCP settings:

{ "mcpServers": { "vap": { "command": "python", "args": ["path/to/mcp/vap_mcp_proxy.py"], "env": { "VAP_API_KEY": "your_api_key" } } } }

Restart your client after configuration.

Available Tools

Tool

What it does

generate_image

Create photorealistic image from text (Flux2 Pro)

generate_video

Create cinematic video from text (Veo 3.1)

generate_music

Create original music from text (Suno V5)

estimate_cost

Preview cost before generating

check_balance

Check your current balance

get_task

Check status of a running task

list_tasks

List your recent tasks

Alternative: Local Proxy

For environments that don't support headers, use the local proxy:

{ "mcpServers": { "vap": { "command": "python", "args": ["/path/to/mcp/vap_mcp_proxy.py"], "env": { "VAP_API_KEY": "your_api_key" } } } }

MCP Registry: io.github.elestirelbilinc-sketch/vap-e


OAuth 2.1 (Enterprise)

For enterprise integrations, VAP supports OAuth 2.1 M2M (machine-to-machine) authentication via Scalekit.

How It Works

OAuth Token → MCP Proxy → Validate → Resolve client_id → Agent → Execute

Setup

# 1. Get OAuth token from your identity provider curl -X POST "https://your-tenant.scalekit.dev/oauth/token" \ -d "grant_type=client_credentials" \ -d "client_id=m2m_xxx" \ -d "client_secret=your_secret" # 2. Link OAuth client to your VAP agent (one-time) curl -X PUT "https://api.vapagent.com/v3/agents/me/oauth" \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{"oauth_client_id": "m2m_xxx"}' # 3. Use OAuth token with MCP # The MCP proxy validates tokens and maps to linked agents

Benefits

  • SSO Integration – Connect VAP to your existing identity provider

  • No API Key in Config – Tokens rotate automatically

  • Audit Trail – OAuth events logged separately


SDK Usage

Installation

pip install vap-sdk

Image Generation

from vape_client import VAPEClient client = VAPEClient(api_key="your_api_key") result = client.generate( description="A serene mountain landscape at sunset" ) print(f"Image URL: {result.image_url}") print(f"Cost: ${result.cost}")

Video Generation

# Generate video with Veo 3.1 video = client.generate_video( prompt="Cinematic aerial shot of coastal cliffs at golden hour", duration=8, aspect_ratio="16:9", generate_audio=True ) print(f"Task ID: {video.task_id}") # Poll for completion task = client.get_task(video.task_id) print(f"Status: {task.status}") print(f"Video URL: {task.result_url}")

Music Generation

# Generate music with Suno V5 music = client.generate_music( prompt="Upbeat indie folk song with acoustic guitar and warm vocals", duration=120, instrumental=False ) print(f"Task ID: {music.task_id}") # Check task status task = client.get_task(music.task_id) print(f"Audio URL: {task.result_url}")

Async Usage

import asyncio from vape_client import AsyncVAPEClient async def main(): async with AsyncVAPEClient(api_key="your_api_key") as client: # Image image = await client.generate(description="A futuristic cityscape") print(f"Image URL: {image.image_url}") # Video video = await client.generate_video(prompt="Ocean waves at sunset") print(f"Video Task: {video.task_id}") # Music music = await client.generate_music(prompt="Lo-fi chill beats") print(f"Music Task: {music.task_id}") asyncio.run(main())

Task Management

# List recent tasks tasks = client.list_tasks(limit=10) for task in tasks.tasks: print(f"{task.task_id}: {task.status} - {task.task_type}") # Get specific task task = client.get_task("your-task-id") print(f"Result: {task.result_url}")

API Endpoints

Endpoint

Method

Description

/v3/generate

POST

Create media execution task

/v3/tasks/{id}

GET

Retrieve task status

/v3/tasks/{id}/result

GET

Retrieve task result

/v3/balance

GET

Check account balance

/v3/agents/me/oauth

PUT

Link OAuth client (Enterprise)

/v3/agents/me/oauth

GET

Check OAuth link status

Full API Docs: api.vapagent.com/docs


The Four Guarantees

1. Pre-Commit Pricing

Every task has a known cost before execution. No surprises.

2. Budget Enforcement

Set a max budget. VAP enforces it. Hit the limit? Task rejected. Balance protected.

3. Failure Ownership

Every task has an explicit owner. Every failure has an address. No more "the agent did something and I don't know what."

4. Deterministic Production Quality

Every output is normalized to broadcast standards. Consistent formats, predictable quality, publish-ready media. No variance between runs.



License

MIT License – see the LICENSE file for details.


VAP Media · Unified MCP Server for AI Agents

"Deterministic media production for AI agents."

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