@daanvanhulsen/figjam-mcp-server
MCP ServerFreeA Figjam MCP server tool, runnable via npx
Capabilities5 decomposed
figjam board state retrieval via mcp protocol
Medium confidenceExposes Figjam board data (frames, shapes, text, connections, metadata) through the Model Context Protocol (MCP) as a standardized tool interface. Implements MCP resource and tool handlers that translate Figma API responses into structured JSON payloads consumable by LLM clients, enabling programmatic read-access to board state without direct API authentication from the client.
Bridges Figjam (visual collaboration tool) with LLM agents via MCP protocol, allowing AI systems to reason about board structure and content without custom API wrappers — implements MCP resource handlers that normalize Figma's hierarchical API into agent-consumable schemas
Simpler than building custom Figma API integrations because MCP standardizes the tool interface; more accessible than direct Figma API calls because it abstracts authentication and response formatting
mcp server lifecycle management and cli invocation
Medium confidenceProvides a runnable MCP server process via npx that handles MCP protocol initialization, message routing, and stdio-based communication with MCP clients. Implements standard MCP server patterns (request/response handlers, resource discovery, tool registration) and exposes the server as a CLI tool, enabling one-command deployment without manual process management or configuration files.
Packages Figjam MCP server as a zero-config npx tool rather than requiring npm install + manual startup scripts, reducing friction for one-off integrations and enabling direct invocation from MCP client configurations
Lower barrier to entry than self-hosted MCP servers because npx handles dependency resolution and process spawning automatically; more portable than Docker-based alternatives for local development
figjam element hierarchy traversal and extraction
Medium confidenceRecursively traverses Figjam board structure (frames, groups, shapes, text nodes) and extracts hierarchical relationships, element properties, and content. Uses Figma API's node tree structure to build a normalized representation of board layout, enabling agents to understand spatial organization, nesting depth, and element relationships without manual parsing of raw API responses.
Implements recursive tree traversal of Figma's node hierarchy specifically optimized for Figjam's collaborative board structure (frames, sticky notes, shapes) rather than generic Figma design files, preserving spatial and semantic relationships
More structured than raw Figma API calls because it normalizes hierarchical relationships; more efficient than manual tree-walking because it handles pagination and deeply nested structures automatically
figjam board content summarization for llm context
Medium confidenceTransforms raw Figjam board state into concise, LLM-friendly summaries that preserve essential information (text content, structure, key elements) while reducing token overhead. Implements content filtering and formatting logic that extracts meaningful board context (sticky notes, text frames, connections) and presents it in a format optimized for LLM reasoning without overwhelming context windows.
Specifically optimizes Figjam board content for LLM consumption by filtering non-essential visual properties and emphasizing collaborative content (sticky notes, text, connections) that carry semantic meaning in a board context
More efficient than passing raw board JSON to LLMs because it reduces token count by 60-80% while preserving actionable content; more context-aware than generic summarization because it understands Figjam's collaborative semantics
figjam board querying and element filtering
Medium confidenceProvides query capabilities to filter and retrieve specific elements from a Figjam board based on criteria (element type, text content, properties, spatial location). Implements filtering logic that works against the extracted board hierarchy, enabling agents to locate relevant elements without full tree traversal and reducing downstream processing overhead.
Implements lightweight in-memory filtering on Figjam board state, allowing agents to locate elements without re-querying the Figma API or traversing the full hierarchy, reducing latency for repeated queries
Faster than re-fetching from Figma API for each query because it operates on cached board state; more flexible than raw API queries because it supports multiple filter dimensions simultaneously
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
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@iflow-mcp/figma-mcp
ModelContextProtocol server for Figma
figma-mcp
ModelContextProtocol server for Figma
figma-mcp-server
A comprehensive local MCP server for Figma. Connect Figma with the Gemini CLI, Cursor, and Claude Desktop.
figma-mcp
ModelContextProtocol for Figma's REST API
cursor-talk-to-figma-mcp
TalkToFigma: MCP integration between AI Agent (Cursor, Claude Code) and Figma, allowing Agentic AI to communicate with Figma for reading designs and modifying them programmatically.
Figma MCP Server
Read Figma designs, components, and design tokens via MCP.
Best For
- ✓AI agents and LLM applications that need to understand Figjam board context
- ✓Teams building Claude/LLM-powered Figjam automation workflows
- ✓Developers integrating Figjam data into multi-step reasoning chains
- ✓Individual developers testing MCP integrations locally
- ✓Teams using Claude Desktop or other MCP-aware IDEs
- ✓Rapid prototyping of Figjam + LLM workflows without infrastructure setup
- ✓AI agents analyzing Figjam boards for content extraction or summarization
- ✓Automation workflows that need to understand board organization before making modifications
Known Limitations
- ⚠Read-only access — cannot modify board state through this capability
- ⚠Requires valid Figma API token with Figjam file access permissions
- ⚠Board state is point-in-time snapshot; no real-time streaming or change subscriptions
- ⚠MCP protocol overhead adds ~100-300ms latency per request depending on board complexity
- ⚠Single-process server — no built-in clustering or horizontal scaling
- ⚠Stdio-based communication limits throughput for high-frequency requests
Requirements
Input / Output
UnfragileRank
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A Figjam MCP server tool, runnable via npx
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