imagine-mcp 1.7.0b8

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

imagine-mcp

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

Image and video understanding + generation for AI agents -- across Gemini, OpenAI, and Grok.

Sister projects from n24q02m (click to expand)

Project	Tagline	Tag
better-code-review-graph	Knowledge graph for token-efficient code reviews -- semantic search and call-...	MCP
better-email-mcp	IMAP/SMTP email for AI agents -- read, send, organize folders, and manage att...	MCP
better-godot-mcp	Composite MCP server for Godot Engine -- 17 composite tools for AI-assisted g...	MCP
better-notion-mcp	Markdown-first Notion for AI agents -- pages, databases, blocks, and comments...	MCP
better-telegram-mcp	Telegram for AI agents -- messages, chats, media, and contacts across both bo...	MCP
claude-plugins	Claude Code plugin marketplace for the n24q02m MCP servers -- install web sea...	Marketplace
imagine-mcp	Image and video understanding + generation for AI agents -- across Gemini, Op...	MCP
jules-task-archiver	Chrome Extension for bulk operations on Jules tasks via batchexecute API -- a...	Tooling
mcp-core	Shared foundation for building MCP servers -- Streamable HTTP transport, OAut...	MCP
mnemo-mcp	Persistent AI memory with hybrid search and embedded sync. Open, free, unlimi...	MCP
qwen3-embed	Lightweight Qwen3 text embedding and reranking via ONNX Runtime and GGUF	Library
skret	Secrets without the server.	CLI
tacet	TACET: a self-distilling neuro-symbolic cascade that amortises LLM cost in kn...	Tooling
web-core	Shared web infrastructure package for search, scraping, HTTP security, and st...	Library
wet-mcp	Open-source MCP server for AI agents: web search, content extraction, and lib...	MCP

Table of contents

• Features
• Status
• Documentation
• Tools
• Comparison
• Security
• Build from Source
• Trust Model
• Contributing
• License

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
• 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
• Dual transport -- pure stdio with provider env vars (default) or HTTP multi-user with paste-token relay form

Status

2026-05-02 -- Architecture stabilization update

Past months saw significant churn around credential handling and the daemon-bridge auto-spawn pattern. This caused multi-process races, browser tab spam, and inconsistent setup UX across plugins. The architecture is now stable: 2 clean modes (stdio + HTTP), no daemon-bridge layer, no auto-spawn from stdio.

Apologies for the instability period. If you encountered issues with prior versions, please update to the latest release and follow the current Setup docs -- most prior workarounds are no longer needed.

Related plugins from the same author:

• wet-mcp -- Web search + content extraction
• mnemo-mcp -- Persistent AI memory
• better-notion-mcp -- Notion API
• better-email-mcp -- Email management
• better-telegram-mcp -- Telegram
• better-godot-mcp -- Godot Engine
• better-code-review-graph -- Code review knowledge graph

All plugins share the same architecture -- install once, learn pattern transfers.

Documentation

Full docs at mcp.n24q02m.com/servers/imagine-mcp/setup/:

• Setup -- install methods for Claude Code, Codex, Gemini CLI, Cursor, Windsurf, mcp.json
• Modes overview -- stdio / local-relay / remote-relay / remote-oauth
• Multi-user setup -- per-JWT-sub credential model

Install with AI agent -- paste this to your AI coding agent:

Install MCP server imagine-mcp following the steps at
https://raw.githubusercontent.com/n24q02m/claude-plugins/main/plugins/imagine-mcp/setup-with-agent.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.
config__open_relay	--	Framework-injected helper (mcp-core) equivalent to config(action="open_relay"); opens the browser credential form.

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

Comparison

How imagine-mcp stacks up against direct competitors in each pillar:

Capability	imagine-mcp	EverArt MCP	fal.ai MCP	Replicate Flux MCP
Image/video understanding	Yes (describe / classify / reason over image + video URLs)	No	No	No
Image generation	Yes (text-to-image + image-to-image via reference_image_url)	Yes (single generate_image)	Yes (text/image-to-image, edit, inpaint)	Yes (single generate_image)
Video generation	Yes (text-to-video + image-to-video, async job_id poll)	No	Yes (text/image-to-video)	No
Multi-provider backends	Yes (Gemini / OpenAI / Grok, auto-fallback)	No (EverArt only)	No (fal.ai only)	No (Replicate Flux only)
Quality/cost tiers	Yes (poor cheap-fast vs rich high-quality per provider)	No	No	No
Self-hostable / open source	Yes (MIT, stdio + HTTP self-host)	Yes (MIT, archived)	Yes (MIT)	Yes (MIT, archived)

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.
• Credential storage -- Credentials submitted through the browser credential form are stored encrypted via mcp-core (AES-GCM, machine-bound key) at ~/.imagine-mcp/config.json.

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

Trust Model

This plugin implements TC-Local (machine-bound, single trust principal). See mcp-core trust model for full classification.

Mode	Storage	Encryption	Who can read your data?
stdio (default)	~/.imagine-mcp/config.json	AES-GCM, machine-bound key	Only your OS user (file perm 0600)
HTTP self-host	Same as stdio	Same	Only you (admin = user)

Contributing

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

License

MIT -- see LICENSE.