MCP Veo

MCP server for Google Veo AI video generation

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "mcp-veo": {
      "command": "uvx",
      "args": [
        "mcp-veo"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Capabilities & Tool Schemas (8)Self-reported

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Veo.

veo_text_to_video

Generate AI video from a text prompt using Veo.

veo_image_to_video

Generate AI video from one or more reference images using Veo.

veo_get_1080p

Get the 1080p high-resolution version of a generated video.

veo_get_task

Query the status and result of a video generation task.

veo_get_tasks_batch

Query multiple video generation tasks at once.

veo_list_models

List all available Veo models and their capabilities.

Documentation Overview

VeoMCP

A Model Context Protocol (MCP) server for AI video generation using Veo through the AceDataCloud API.

Generate AI videos from text prompts or images directly from Claude, VS Code, or any MCP-compatible client.

Features

Text to Video - Create AI-generated videos from text descriptions
Image to Video - Animate images or create transitions between images
Multi-Image Fusion - Blend elements from multiple images
1080p Upscaling - Get high-resolution versions of generated videos
Task Tracking - Monitor generation progress and retrieve results
Multiple Models - Choose between quality and speed with various Veo models

Tool Reference

Tool	Description
`veo_text_to_video`	Generate AI video from a text prompt using Veo.
`veo_image_to_video`	Generate AI video from one or more reference images using Veo.
`veo_get_1080p`	Get the 1080p high-resolution version of a generated video.
`veo_get_task`	Query the status and result of a video generation task.
`veo_get_tasks_batch`	Query multiple video generation tasks at once.
`veo_list_models`	List all available Veo models and their capabilities.
`veo_list_actions`	List all available Veo API actions and corresponding tools.
`veo_get_prompt_guide`	Get guidance on writing effective prompts for Veo video generation.

Quick Start

1. Get Your API Token

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

Endpoint: https://veo.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

Go to Claude.ai Settings → Integrations → Add More
Enter the server URL: https://veo.mcp.acedata.cloud/mcp
Complete the OAuth login flow
Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

config.json

{
  "servers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
Click Add → HTTP
Paste:

config.json

{
  "mcpServers": {
    "veo": {
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

Terminal

claude mcp add veo --transport http https://veo.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

yaml

mcpServers:
  - name: veo
    type: streamable-http
    url: https://veo.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

config.json

{
  "language_models": {
    "mcp_servers": {
      "veo": {
        "url": "https://veo.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

bash

# Health check (no auth required)
curl https://veo.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://veo.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

server.ts

# Install from PyPI
pip install mcp-veo
# or
uvx mcp-veo

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-veo

# Run (HTTP mode for remote access)
mcp-veo --transport http --port 8000

Claude Desktop (Local)

config.json

{
  "mcpServers": {
    "veo": {
      "command": "uvx",
      "args": ["mcp-veo"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

Terminal

docker pull ghcr.io/acedatacloud/mcp-veo:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-veo:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Tools

Video Generation

Tool	Description
`veo_text_to_video`	Generate video from a text prompt
`veo_image_to_video`	Generate video from reference image(s)
`veo_get_1080p`	Get high-resolution 1080p version

Tasks

Tool	Description
`veo_get_task`	Query a single task status
`veo_get_tasks_batch`	Query multiple tasks at once

Information

Tool	Description
`veo_list_models`	List available Veo models
`veo_list_actions`	List available API actions
`veo_get_prompt_guide`	Get video prompt writing guide

Usage Examples

Generate Video from Text

Code

User: Create a video of a sunset over the ocean

Claude: I'll generate a sunset video for you.
[Calls veo_text_to_video with prompt="Cinematic shot of a golden sunset over the ocean, waves gently rolling, warm colors reflecting on the water"]

Animate an Image

Code

User: Animate this product image to make it rotate slowly

Claude: I'll create a video from your image.
[Calls veo_image_to_video with image_urls=["product_image.jpg"], prompt="Product slowly rotates 360 degrees, studio lighting"]

Create Image Transition

Code

User: Create a video that transitions between these two landscape photos

Claude: I'll create a transition video between your images.
[Calls veo_image_to_video with image_urls=["img1.jpg", "img2.jpg"], prompt="Smooth cinematic transition between scenes"]

Available Models

Model	Text2Video	Image2Video	Image Input
`veo3`	✅	✅	1-3 images
`veo3-fast`	✅	✅	1-3 images
`veo31`	✅	✅	1-3 images
`veo31-fast`	✅	✅	1-3 images
`veo31-fast-ingredients`	❌	✅	1-3 images (fusion)

Aspect Ratios:

16:9 - Landscape/widescreen (default)
9:16 - Portrait/vertical (social media)

Configuration

Environment Variables

Read the full README →View source on GitHub →

Related MCP Servers

View all in Multimedia Process View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

28d ago

Most recent push to the default branch.

Tools exposed

Callable tools this server registers over MCP.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Veo

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "mcp-veo": { "command": "uvx", "args": ["mcp-veo"] } }

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Technical Specs & Signals

CategoryMultimedia Process

11/12 checks healthy over the last 46d

51Quality signal: Good · 51/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity5/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 2d ago via OSV.dev · mcp-veo (PyPI)

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More in 🎥 Multimedia Process →Best MCP servers for Multimedia & Media Processing →Best Google Workspace MCP servers →Alternatives to MCP Veo →Install in Claude Desktop Install in Cursor Install in VS Code Setup guides for all 13 MCP clients

MCP Veo

MCP server for Google Veo AI video generation

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "mcp-veo": {
      "command": "uvx",
      "args": [
        "mcp-veo"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Capabilities & Tool Schemas (8)Self-reported

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Veo.

veo_text_to_video

Generate AI video from a text prompt using Veo.

veo_image_to_video

Generate AI video from one or more reference images using Veo.

veo_get_1080p

Get the 1080p high-resolution version of a generated video.

veo_get_task

Query the status and result of a video generation task.

veo_get_tasks_batch

Query multiple video generation tasks at once.

veo_list_models

List all available Veo models and their capabilities.

Documentation Overview

VeoMCP

A Model Context Protocol (MCP) server for AI video generation using Veo through the AceDataCloud API.

Generate AI videos from text prompts or images directly from Claude, VS Code, or any MCP-compatible client.

Features

Text to Video - Create AI-generated videos from text descriptions
Image to Video - Animate images or create transitions between images
Multi-Image Fusion - Blend elements from multiple images
1080p Upscaling - Get high-resolution versions of generated videos
Task Tracking - Monitor generation progress and retrieve results
Multiple Models - Choose between quality and speed with various Veo models

Tool Reference

Tool	Description
`veo_text_to_video`	Generate AI video from a text prompt using Veo.
`veo_image_to_video`	Generate AI video from one or more reference images using Veo.
`veo_get_1080p`	Get the 1080p high-resolution version of a generated video.
`veo_get_task`	Query the status and result of a video generation task.
`veo_get_tasks_batch`	Query multiple video generation tasks at once.
`veo_list_models`	List all available Veo models and their capabilities.
`veo_list_actions`	List all available Veo API actions and corresponding tools.
`veo_get_prompt_guide`	Get guidance on writing effective prompts for Veo video generation.

Quick Start

1. Get Your API Token

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

Endpoint: https://veo.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

Go to Claude.ai Settings → Integrations → Add More
Enter the server URL: https://veo.mcp.acedata.cloud/mcp
Complete the OAuth login flow
Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

config.json

{
  "servers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
Click Add → HTTP
Paste:

config.json

{
  "mcpServers": {
    "veo": {
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

Terminal

claude mcp add veo --transport http https://veo.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

config.json

{
  "mcpServers": {
    "veo": {
      "type": "streamable-http",
      "url": "https://veo.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

yaml

mcpServers:
  - name: veo
    type: streamable-http
    url: https://veo.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

config.json

{
  "language_models": {
    "mcp_servers": {
      "veo": {
        "url": "https://veo.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

bash

# Health check (no auth required)
curl https://veo.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://veo.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

server.ts

# Install from PyPI
pip install mcp-veo
# or
uvx mcp-veo

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-veo

# Run (HTTP mode for remote access)
mcp-veo --transport http --port 8000

Claude Desktop (Local)

config.json

{
  "mcpServers": {
    "veo": {
      "command": "uvx",
      "args": ["mcp-veo"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

Terminal

docker pull ghcr.io/acedatacloud/mcp-veo:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-veo:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Tools

Video Generation

Tool	Description
`veo_text_to_video`	Generate video from a text prompt
`veo_image_to_video`	Generate video from reference image(s)
`veo_get_1080p`	Get high-resolution 1080p version

Tasks

Tool	Description
`veo_get_task`	Query a single task status
`veo_get_tasks_batch`	Query multiple tasks at once

Information

Tool	Description
`veo_list_models`	List available Veo models
`veo_list_actions`	List available API actions
`veo_get_prompt_guide`	Get video prompt writing guide

Usage Examples

Generate Video from Text

Code

User: Create a video of a sunset over the ocean

Claude: I'll generate a sunset video for you.
[Calls veo_text_to_video with prompt="Cinematic shot of a golden sunset over the ocean, waves gently rolling, warm colors reflecting on the water"]

Animate an Image

Code

User: Animate this product image to make it rotate slowly

Claude: I'll create a video from your image.
[Calls veo_image_to_video with image_urls=["product_image.jpg"], prompt="Product slowly rotates 360 degrees, studio lighting"]

Create Image Transition

Code

User: Create a video that transitions between these two landscape photos

Claude: I'll create a transition video between your images.
[Calls veo_image_to_video with image_urls=["img1.jpg", "img2.jpg"], prompt="Smooth cinematic transition between scenes"]

Available Models

Model	Text2Video	Image2Video	Image Input
`veo3`	✅	✅	1-3 images
`veo3-fast`	✅	✅	1-3 images
`veo31`	✅	✅	1-3 images
`veo31-fast`	✅	✅	1-3 images
`veo31-fast-ingredients`	❌	✅	1-3 images (fusion)

Aspect Ratios:

16:9 - Landscape/widescreen (default)
9:16 - Portrait/vertical (social media)

Configuration

Environment Variables

Read the full README →View source on GitHub →

Related MCP Servers

View all in Multimedia Process View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

28d ago

Most recent push to the default branch.

Tools exposed

Callable tools this server registers over MCP.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Veo

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "mcp-veo": { "command": "uvx", "args": ["mcp-veo"] } }

AllMCPs Directory Badge

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Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

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Markdown (GitHub README)

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HTML Embed

<a href="https://allmcps.com/mcp/mcp-veo"><img src="https://allmcps.com/api/badge/mcp-veo?style=directory" alt="MCP Veo on AllMCPs" /></a>

Technical Specs & Signals

CategoryMultimedia Process

11/12 checks healthy over the last 46d

51Quality signal: Good · 51/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity5/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 2d ago via OSV.dev · mcp-veo (PyPI)

★ Spotlight Slot

Feature Your MCP Server

Get maximum visibility for your server across our directory, search results, and detail pages.

Spotlight Your Server

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.