This Figma MCP Server with Chunking provides efficient, memory-aware access to Figma files and metadata, offering:
- Retrieve Figma file data with chunking, pagination, and resume capabilities
- List files within a project or team
- Access version history of Figma files
- Retrieve comments on Figma files
- Extract components and styles from Figma files
- Fetch specific nodes by ID
- Configure memory usage limits and chunk sizes
- Filter nodes by type and control traversal depth
- Exclude unnecessary properties from responses
- Monitor memory usage and progress during operations
- Debug logging for troubleshooting
Provides tools for interacting with the Figma API, including file data retrieval, file listing, version history, comment management, component and style retrieval, with memory-efficient chunking and pagination capabilities for handling large Figma files.
Figma MCP Server with Chunking
A Model Context Protocol (MCP) server for interacting with the Figma API, featuring memory-efficient chunking and pagination capabilities for handling large Figma files.
Overview
This MCP server provides a robust interface to the Figma API with built-in memory management features. It's designed to handle large Figma files efficiently by breaking down operations into manageable chunks and implementing pagination where necessary.
Key Features
- Memory-aware processing with configurable limits
- Chunked data retrieval for large files
- Pagination support for all listing operations
- Node type filtering
- Progress tracking
- Configurable chunk sizes
- Resume capability for interrupted operations
- Debug logging
- Config file support
Installation
Installing via Smithery
To install Figma MCP Server with Chunking for Claude Desktop automatically via Smithery:
Manual Installation
Configuration
Environment Variables
FIGMA_ACCESS_TOKEN
: Your Figma API access token
Config File
You can provide configuration via a JSON file using the --config
flag:
Usage:
Tools
get_file_data (New)
Retrieves Figma file data with memory-efficient chunking and pagination.
Response:
list_files
Lists files with pagination support.
get_file_versions
Retrieves version history in chunks.
get_file_comments
Retrieves comments with pagination.
get_file_info
Retrieves file information with chunked node traversal.
get_components
Retrieves components with chunking support.
get_styles
Retrieves styles with chunking support.
get_file_nodes
Retrieves specific nodes with chunking support.
Memory Management
The server implements several strategies to manage memory efficiently:
Chunking Strategy
- Configurable chunk sizes via
pageSize
- Memory usage monitoring
- Automatic chunk size adjustment based on memory pressure
- Progress tracking per chunk
- Resume capability using cursors
Best Practices
- Start with smaller chunk sizes (50-100 nodes) and adjust based on performance
- Monitor memory usage through the response metadata
- Use node type filtering when possible to reduce data load
- Implement pagination for large datasets
- Use the resume capability for very large files
Configuration Options
pageSize
: Number of nodes per chunk (default: 100)maxMemoryMB
: Maximum memory usage in MB (default: 512)nodeTypes
: Filter specific node typesdepth
: Control traversal depth for nested structures
Debug Logging
The server includes comprehensive debug logging:
Error Handling
The server provides detailed error messages and suggestions:
Troubleshooting
Common Issues
- Memory Errors
- Reduce chunk size
- Use node type filtering
- Implement pagination
- Specify smaller depth values
- Performance Issues
- Monitor memory usage
- Adjust chunk sizes
- Use appropriate node type filters
- Implement caching for frequently accessed data
- API Limits
- Implement rate limiting
- Use pagination
- Cache responses when possible
Debug Mode
Enable debug logging for detailed information:
Contributing
Contributions are welcome! Please read our contributing guidelines and submit pull requests to our repository.
License
This project is licensed under the MIT License - see the LICENSE file for details.
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Tools
A Model Context Protocol server for interacting with the Figma API that handles large Figma files efficiently through memory-aware chunking and pagination capabilities.
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