How do I install Imagine?

Imagine is a local plugin. Install it using PyPI package: imagine-mcp and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

What credentials does Imagine need?

Imagine requires the following credentials or environment variables: GOOGLE_AI_STUDIO_API_KEY, OPENAI_API_KEY, XAI_API_KEY. You can find setup instructions on the server detail page.

What AI apps work with Imagine?

Imagine uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Imagine MCP Server

by N24q02m

Developer ToolsLow Risk10.0MCP RegistryLocal

Free

Server data from the Official MCP Registry

MCP server for image/video understanding & generation (Gemini/OpenAI/Grok)

About

MCP server for image/video understanding & generation (Gemini/OpenAI/Grok)

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (1 strong, 2 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (11/12 approved).

8 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

What You'll Need

Set these up before or after installing:

Google AI Studio API key (aistudio.google.com/apikey)Required

Environment variable: GOOGLE_AI_STUDIO_API_KEY

OpenAI API key (platform.openai.com)Required

Environment variable: OPENAI_API_KEY

xAI (Grok) API key (console.x.ai)Required

Environment variable: XAI_API_KEY

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-n24q02m-imagine-mcp": {
      "env": {
        "XAI_API_KEY": "your-xai-api-key-here",
        "OPENAI_API_KEY": "your-openai-api-key-here",
        "GOOGLE_AI_STUDIO_API_KEY": "your-google-ai-studio-api-key-here"
      },
      "args": [
        "imagine-mcp"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

imagine-mcp

mcp-name: io.github.n24q02m/imagine-mcp

Production-grade MCP server for image and video understanding + generation across Gemini, OpenAI, and Grok.

Features

Multimodal understanding -- Describe, classify, or reason over images and videos (Gemini handles mixed image + video in one call)
Image generation -- Text-to-image and image-to-image (edit / inpaint) across Gemini Imagen, OpenAI gpt-image, Grok Imagine
Video generation -- Text-to-video and image-to-video (Gemini Veo 3.1, Grok Imagine Video)
3 providers x 2 tiers -- Same interface for gemini / openai / grok at poor (cheap/fast) or rich (high quality); swap via parameter
Leaderboard-ranked models -- Provider ordering auto-refreshed weekly from Artificial Analysis + LMArena leaderboards
Zero-config onboarding -- Browser-based credential relay form; no .env files or manual credential plumbing
Degraded mode -- Server starts with zero credentials and surfaces remaining providers as you add keys
Response cache -- Disk-based caching of understand responses with configurable TTL
Smart stdio proxy -- stdio transport spawns a local HTTP daemon and forwards JSON-RPC frames, sharing credentials across invocations

Setup

With AI Agent -- copy and send this to your AI agent:

Please set up imagine-mcp for me. Follow this guide: https://raw.githubusercontent.com/n24q02m/imagine-mcp/main/docs/setup-with-agent.md

Manual setup -- follow docs/setup-manual.md

Tools

Tool	Actions	Description
`understand`	--	Describe or reason over one or more image/video URLs. `media_urls: list[str]`, `prompt: str`, `provider`, `tier`, `max_tokens`.
`generate`	--	Generate an image or video from a text prompt. `media_type: image\|video`, optional `reference_image_url`, optional `job_id` (video poll), `aspect_ratio`, `duration_seconds`.
`config`	`open_relay`, `relay_status`, `relay_skip`, `relay_reset`, `relay_complete`, `warmup`, `status`, `set`, `cache_clear`	Credential + runtime config: open relay form, check credential state, set runtime knobs (log level, default provider, TTL), clear response cache.
`help`	--	Full Markdown documentation for `understand`, `generate`, or `config` topics.

Model IDs per provider x action x tier are leaderboard-ranked; see docs/models.md (auto-regenerated from src/imagine_mcp/models.py).

Security

SSRF + LFI prevention -- All media_urls and reference_image_url are validated at the dispatch boundary; only http:// and https:// schemes reach the providers. file://, ftp://, gopher://, and scheme-less URLs are rejected.
No credentials in errors -- Provider-side errors are sanitized before being returned.
Degraded start -- Missing credentials do not prevent the server from starting; affected actions surface actionable errors instead of crashing at boot.
Relay transport -- Credentials submitted through the local relay form are stored encrypted via mcp-core (config.enc, user-scoped platformdirs).

Build from Source

git clone https://github.com/n24q02m/imagine-mcp.git
cd imagine-mcp
mise run setup      # or: uv sync --group dev
mise run dev        # run http local relay daemon

Contributing

See CONTRIBUTING.md for the full development workflow, commit convention, and release process. Issues + Discussions welcome.

License

MIT -- see LICENSE.

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Imagine MCP Server

About

Security Report

Findings (1)

Permissions Required

What You'll Need

How to Install

Documentation

imagine-mcp

Features

Setup

Tools

Security

Build from Source

Contributing

License

Reviews

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