Project description
imagine-mcp
mcp-name: io.github.n24q02m/imagine-mcp
Image and video understanding + generation for AI agents — across Gemini, OpenAI, and Grok.
इससे जुड़ी जानकारी
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Table of contents
- Features
- Install
- Smithery
- Configuration
- CLI
- Hosted endpoint
- Documentation
- Tools
- Comparison
- Security
- Build from Source
- Deploy to Cloudflare
- 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/grokatpoor(cheap/fast) orrich(high quality); swap via parameter - Open model passthrough — Understanding routes through litellm; pass any
provider/model, or configure an ordered model chain (no hardcoded catalog) - Degraded mode — Server starts with zero credentials and surfaces remaining providers as you add keys
- Response cache — Disk-based caching of
understandresponses with configurable TTL - Dual transport — pure stdio with provider env vars (default) or HTTP multi-user with paste-token relay form
Install
Run with uvx (no install step) or pull the container image:
# uvx -- recommended, runs the published PyPI ...
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