Recraft AI▌
by recraft-ai
Recraft AI is an ai image generator for creating, editing, and upscaling raster or vector images with advanced artificia
Integrates with Recraft's image generation API to create and edit raster and vector images, apply custom styles, manipulate backgrounds, upscale images, and perform vectorization with fine-grained control over artistic properties.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Designers creating custom artwork and illustrations
- / Content creators needing both raster and vector assets
- / Developers building image-heavy applications
- / Anyone requiring high-quality image generation with style control
capabilities
- / Generate raster and vector images from text prompts
- / Edit existing images with precise modifications
- / Create custom artistic styles for image generation
- / Remove and replace image backgrounds
- / Upscale raster images to higher resolutions
- / Convert raster images to vector format
what it does
Connects to Recraft's API to generate, edit, and manipulate both raster and vector images with fine-grained artistic control.
about
Recraft AI is an official MCP server published by recraft-ai that provides AI assistants with tools and capabilities via the Model Context Protocol. Recraft AI is an ai image generator for creating, editing, and upscaling raster or vector images with advanced artificia It is categorized under ai ml, design.
how to install
You can install Recraft AI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Recraft AI is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
- style
- size
- model
- number of images | \$0.04/\$0.08 per raster/vector image | | `create_style` | Creates a style from the list of images | - list of images
- basic style | \$0.04 | | `vectorize_image` | Vectorizes raster image | - image | \$0.01 | | `image_to_image` | Generates raster/vector images from image and prompt | - image
- prompt
- similarity strength
- style
- size
- model
- number of images | \$0.04/\$0.08 per raster/vector image | | `remove_background` | Removes background in image | - image | \$0.01 | | `replace_background` | Generates new background in image from prompt | - image
- prompt for background
- style
- size
- model
- number of images | \$0.04/\$0.08 per raster/vector image | | `crisp_upscale` | Crisp upscale of image | - image | \$0.004 | | `creative_upscale` | Creative upscale of image | - image | \$0.25 | | `get_user` | Get information about the user and left balance | | | You can find the detailed explanation of tools, their parameters, and prices in [Recraft API docs](https://recraft.ai/docs).
FAQ
- What is the Recraft AI MCP server?
- Recraft AI is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Recraft AI?
- This profile displays 74 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★74 reviews- ★★★★★Michael Patel· Dec 24, 2024
According to our notes, Recraft AI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Chinedu Chawla· Dec 24, 2024
We evaluated Recraft AI against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Dhruvi Jain· Dec 12, 2024
Recraft AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Isabella Zhang· Dec 12, 2024
Recraft AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Pratham Ware· Dec 8, 2024
According to our notes, Recraft AI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Luis Verma· Dec 8, 2024
I recommend Recraft AI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Kofi Abbas· Nov 27, 2024
Recraft AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Zara Menon· Nov 15, 2024
We wired Recraft AI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Oshnikdeep· Nov 3, 2024
I recommend Recraft AI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Fatima Taylor· Nov 3, 2024
I recommend Recraft AI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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