How do I use Agnes MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Agnes MCP Server Generate an image of a futuristic city at sunset, 1920x1080" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Agnes MCP Server

by zssty2010

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

Agnes MCP Server

An MCP (Model Context Protocol) server that wraps the Agnes AI image and video generation APIs, enabling AI assistants (Claude, Cursor, VS Code, etc.) to generate images and videos via standardized tool calls.

Features

Image Generation — Text-to-image and image-to-image via generate_image
Video Generation — Text-to-video and image-to-video via generate_video + get_video
Two Transport Modes — stdio (local) and Streamable HTTP (remote)
Auto Download — Optionally save generated media to disk automatically
Blocking & Async — wait=true for synchronous generation, or poll with get_video

Related MCP server: ImaginePro MCP Server

Quick Start

1. Install Dependencies

cd agnes-mcp-server
npm install
npm run build

2. Set API Key

export AGNES_API_KEY="sk-agnes-your-api-key-here"

3. Run the Server

Stdio mode (default, for local MCP clients like Claude Desktop, Cursor):

npm run start
# or
node agnes-mcp-server.cjs

Streamable HTTP mode (for remote MCP clients):

MCP_TRANSPORT=http npm run start:http
# Default port: 3100 (configurable via HTTP_PORT)

4. Configure Your MCP Client

Add this to your MCP client configuration (e.g., .mcp.json):

{
  "mcpServers": {
    "agnes": {
      "command": "node",
      "args": ["agnes-mcp-server.cjs"],
      "env": {
        "AGNES_API_KEY": "sk-agnes-your-api-key-here"
      }
    }
  }
}

Available Tools

Tool	Description
`generate_image`	Generate or edit an image. Supports text-to-image and image-to-image modes.
`generate_video`	Submit a video generation task. Set `wait=true` to block until complete.
`get_video`	Query video generation status and optionally download the result.

Tool Parameters

generate_image

Parameter	Type	Required	Default	Description
`prompt`	string	Yes	—	Text description of the desired image
`size`	string	No	`1024x1024`	Image dimensions (e.g., `512x512`, `1024x1024`)
`images`	string[]	No	—	Input images (local file paths or base64 data URIs)
`format`	`"url"` \| `"b64"`	No	`url`	Output format when no `outputDir` is set
`outputDir`	string	No	—	Directory to download the image file

generate_video

Parameter	Type	Required	Default	Description
`prompt`	string	Yes	—	Text description of the desired video
`image`	string \| string[]	No	—	Input image(s) for image-to-video mode
`mode`	string	No	—	Generation mode (e.g., `"image-to-video"`)
`width`	number	No	—	Video width
`height`	number	No	—	Video height
`num_frames`	number	No	—	Number of frames
`frame_rate`	number	No	—	Frames per second
`seed`	number	No	—	Random seed for reproducibility
`negative_prompt`	string	No	—	Things to exclude from the video
`outputDir`	string	No	—	Directory to download the video file
`wait`	boolean	No	`false`	Block until generation completes

get_video

Parameter	Type	Required	Default	Description
`videoId`	string	Yes	—	Video ID returned by `generate_video`
`taskId`	string	No	—	Task ID (fallback for querying)
`outputDir`	string	No	—	Directory to download the video file

Environment Variables

Variable	Required	Default	Description
`AGNES_API_KEY`	Yes	—	Your Agnes API key (starts with `sk-`)
`MCP_TRANSPORT`	No	`stdio`	Transport mode: `stdio` or `http`
`HTTP_PORT`	No	`3100`	HTTP server port (only in `http` mode)
`DEFAULT_DOWNLOAD_DIR`	No	—	Root directory for auto-downloaded media

Project Structure

agnes-mcp-server/
├── src/
│   ├── app/               # Server entry points (stdio, http, bundle)
│   ├── client/            # HTTP client wrapper
│   ├── core/              # Core MCP setup and registry
│   ├── module/
│   │   ├── image/         # Image generation service
│   │   └── video/         # Video generation service
│   ├── providers/         # API providers (AgnesClient, image, video)
│   ├── tools/             # MCP tool implementations
│   └── types/             # Shared types and result formatters
├── agnes-mcp-server.cjs   # Bundled entry point
├── agnes-bundle.cjs       # Standalone bundle
├── SKILL.md               # MCP skill definition
├── TOKEN_AUTH.md          # Authentication documentation
└── package.json

Development

# Watch mode (TypeScript → Node)
npm run dev

# Build TypeScript
npm run build

# Create standalone bundle
npm run bundle

# Run smoke test
npm run test

Test Script

A standalone test script is included for verifying the image-to-video API flow:

npx tsx test-video-image.ts <local-image-path> <api-key>
# or
IMAGE_PATH=test.jpg AGNES_API_KEY=sk-xxx npx tsx test-video-image.ts

License

MIT

Install Server

license - not found

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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