Picsart GenAI MCP

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MCP Quickstart ​

The Picsart MCP server exposes the full model catalog as Model Context Protocol tools. Connect it to any MCP-compatible agent and that agent can generate image, video, and audio across 174 models using natural language or structured tool calls.

New to MCP? Start with What is MCP? first.

Prerequisites ​

1. Install the gen-ai CLI — see Installation.
2. Run gen-ai login once (opens your browser for OAuth).

That is all. The MCP server (gen-ai-mcp) ships with the CLI and uses the same credentials.

Connect to your agent ​

Claude Code ​

bash

claude mcp add picsart-gen-ai -- gen-ai-mcp

Then use it in any conversation:

"Generate a product image on a white background using Flux 2 Pro, 4:3 aspect ratio."

For full Claude Code setup including Skills and troubleshooting, see Claude Code integration.

Cursor ​

Add the following to your Cursor MCP configuration file (.cursor/mcp.json or equivalent):

json

{
  "mcpServers": {
    "picsart-gen-ai": {
      "command": "gen-ai-mcp"
    }
  }
}

See Cursor integration.

Windsurf ​

Add to your Windsurf MCP config:

json

See Windsurf integration.

VS Code (Copilot) ​

Add to .vscode/mcp.json in your workspace or to your user settings:

json

{
  "servers": {
    "picsart-gen-ai": {
      "type": "stdio",
      "command": "gen-ai-mcp"
    }
  }
}

See VS Code integration.

Codex (OpenAI) ​

bash

codex mcp add picsart-gen-ai -- gen-ai-mcp

See Codex integration.

ChatGPT and other MCP clients ​

See ChatGPT integration or the official page at picsart.com/gen-ai-mcp for the current connector config.

---

Tool catalog ​

Every tool is available to the agent once connected. Tools that do not spend credits are free to call as many times as needed.

Tool	What it does	Credits
picsart_list_models	Browse the catalog; filter by mode or provider	no
picsart_model_catalog	Full catalog as data for agent reasoning (no widget)	no
picsart_model_params	JSON schema of a model's accepted parameters	no
picsart_preflight	Validate params and return a credit estimate (dry run)	no
picsart_generate	Run any model end-to-end	yes
picsart_remove_bg	Remove an image background	yes
picsart_change_bg	Replace an image background	yes
picsart_enhance	Upscale or enhance an image	yes
picsart_vectorize	Convert a raster image to SVG	yes
picsart_music_studio	Browse music models and prompt-builder metadata	no
picsart_credits	Current credit balance	no
picsart_drive	List, upload, organize, and manage Drive files	yes

picsart_preflight is a dry run — it validates parameters and returns a credit estimate without invoking any model or spending credits.

Recommended generation flow ​

The tools are designed to chain. This sequence avoids surprises:

1. picsart_list_models — pick a model.
2. picsart_model_params — see what parameters it accepts.
3. picsart_preflight — validate the payload and confirm the credit cost.
4. picsart_generate — run it.

Agents that skip to step 5 directly will still work, but they may use a suboptimal model or parameter set.

Example tool calls ​

Generate an image:

json

{
  "name": "picsart_generate",
  "arguments": {
    "model": "flux-2-pro",
    "prompt": "a ceramic cup, studio lighting, 4:3",
    "aspectRatio": "4:3",
    "count": 1
  }
}

Generate a video:

json

{
  "name": "picsart_generate",
  "arguments": {
    "model": "seedance-2.0",
    "prompt": "a cat skiing down a mountain",
    "duration": 8,
    "aspectRatio": "16:9",
    "generateAudio": true
  }
}

Quote a cost before generating:

json

{
  "name": "picsart_preflight",
  "arguments": {
    "model": "veo-3.1",
    "params": { "duration": 8, "resolution": "1080p" }
  }
}

Remove a background:

json

{
  "name": "picsart_remove_bg",
  "arguments": {
    "imageUrls": ["https://example.com/product.jpg"]
  }
}

Inputs reference ​

picsart_generate takes:

• Required: model (model id), prompt (text prompt)
• Common optional: aspectRatio, resolution, duration, count (1 to 8), quality, style, negativePrompt
• Image input: imageUrls (array of URLs — for image-to-image or image-to-video models)
• Video input: videoUrl (single URL — for video-to-video models)
• Audio generation: generateAudio (boolean — for video models that support native audio)
• Prompt enhancement: enhancePrompt (boolean — routes through an LLM before generation)
• Model-specific params: extra (free-form object — use picsart_model_params to see what a model accepts)

Results come back as results: [{ url, metadata? }]. Assets are URLs, never base64. Each result also includes a resource_link so the agent can reference it in follow-up tool calls.

FAQ ​

Does the MCP server require a separate API key?

No. It uses the same OAuth session as the CLI. Run gen-ai login once; the MCP server picks up those credentials automatically.

Can I use MCP and the CLI on the same machine at the same time?

Yes. Both use the same credentials file (~/.gen-ai/credentials.json) and the same credit balance. Running them in parallel is fine.

The agent connected but the tools do not appear.

Restart the agent after adding the MCP config. Most agents load the tool list at startup, not dynamically.

Which models work via MCP?

All 174 models in the catalog. There is no MCP-specific subset. Use picsart_list_models to filter by mode or provider, or browse the Model Catalog.

Can the agent save generated files to Drive?

Yes. Pass "saveToDrive": true in the picsart_generate arguments, or use picsart_drive to upload a local file or URL. See Files and Drive.

How do I know what a model costs before running it?

Call picsart_preflight with the model id and the parameters you plan to use. It validates the payload and returns a credit estimate without running the generation.

What happens if my credit balance runs out mid-generation?

Check your balance with picsart_credits and top up at picsart.com before retrying.