Which integrations are available for this server?

Allows AI agents to read, inspect, and export from Figma files programmatically.

How do I use figma-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@figma-mcp Export frame 1:42 as SVG" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

figma-mcp

by Anakintano

Overview Schema Related Servers Score Discussions

Python

Remote

What is this?

figma-mcp is a Model Context Protocol server that gives LLM agents (Claude, GPT, etc.) the ability to read, inspect, and export from Figma files programmatically.

Built with the official MCP Python SDK using the FastMCP API.

Related MCP server: Figma MCP Server

Architecture

┌─────────────────────┐
│  Claude Desktop /   │
│  Any MCP Client     │
└────────┬────────────┘
         │ stdio
┌────────▼────────────┐
│  figma-mcp Server   │
│  (FastMCP)          │
└────────┬────────────┘
         │ HTTPS
┌────────▼────────────┐
│  Figma REST API     │
│  api.figma.com/v1   │
└─────────────────────┘

Project structure:

src/figma_mcp/
  __init__.py        # Entry point
  config.py          # Environment config (dotenv)
  utils.py           # Logger (stderr) + validation helpers
  figma_client.py    # Figma API client (requests)
  server.py          # FastMCP server + all tool definitions

Installation

git clone https://github.com/Anakintano/figma-mcp.git
cd figma-mcp
pip install -e .

Or with uv (recommended):

uv pip install -e .

Configuration

1. Get a Figma Token

Go to Figma Settings → Account → Personal access tokens
Click Generate new token
Copy the token

2. Set Environment Variable

Create a .env file in the project root:

FIGMA_ACCESS_TOKEN=figd_your_token_here

3. Claude Desktop Setup

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "figma": {
      "command": "python",
      "args": ["-m", "figma_mcp"],
      "cwd": "/path/to/figma-mcp",
      "env": {
        "FIGMA_ACCESS_TOKEN": "figd_your_token_here"
      }
    }
  }
}

Tools

Tool	Description	Key Params
`get_figma_file`	Get a complete Figma file	`file_key`
`get_frame_nodes`	Get specific nodes/frames	`file_key`, `node_ids`
`list_components`	List all components	`file_key`
`list_styles`	List all styles	`file_key`
`export_assets`	Export as PNG/JPG/SVG/PDF	`file_key`, `node_ids`, `format`, `scale`

Finding your file key: In any Figma URL like https://www.figma.com/file/ABC123xyz/My-Design, the file key is ABC123xyz.

Use Cases

1. Design System Audit

Prompt: "List all components in my Figma file abc123 and tell me which ones don't follow our naming convention"

The agent uses list_components to fetch every component, then analyzes naming patterns — great for enforcing consistency across large design systems.

2. Developer Handoff

Prompt: "Get the layout details of the login page frame 1:42 from file xyz789"

Uses get_frame_nodes to extract exact positions, sizes, colors, fonts, and spacing — giving developers precise specs without leaving the chat.

3. Asset Export Pipeline

Prompt: "Export all icon frames 1:10, 1:11, 1:12 as SVGs from file abc123"

The agent calls export_assets with format=svg and returns download URLs for each icon, ready for use in code.

4. Style Token Extraction

Prompt: "What are all the color and text styles in file myDesign? Format them as CSS variables"

Uses list_styles to pull every defined style, then the LLM formats them into usable CSS custom properties:

--color-primary: #3B82F6;
--color-secondary: #10B981;
--font-heading: Inter, 24px, 700;

5. Design Review / QA

Prompt: "Get the full structure of file abc123 and check if all frames have consistent padding"

Fetches the entire file with get_figma_file, then the LLM traverses the node tree to flag layout inconsistencies.

6. Multi-File Comparison

Prompt: "Compare the components in file designV1 vs designV2 and list what changed"

Calls list_components on both files, and the LLM diffs the results to produce a changelog of design changes.

Example Prompts

Here are ready-to-use prompts for Claude Desktop with this MCP server:

"Get the structure of my Figma file with key abc123XYZ"

"Show me all components in this design file"

"Export frame 1:42 as an SVG"

"What text styles are defined in this design?"

"Extract the layout specs for nodes 1:2 and 3:4"

"List all color styles and convert them to a Tailwind config"

"Get the login page frame and describe the UI elements"

API Reference

get_figma_file

Param	Type	Description
`file_key`	`str`	Figma file key

get_frame_nodes

Param	Type	Description
`file_key`	`str`	Figma file key
`node_ids`	`list[str]`	Node IDs (e.g., `["1:2", "3:4"]`)

list_components

Param	Type	Description
`file_key`	`str`	Figma file key

list_styles

Param	Type	Description
`file_key`	`str`	Figma file key

export_assets

Param	Type	Description
`file_key`	`str`	Figma file key
`node_ids`	`list[str]`	Node IDs to export
`format`	`str`	`png`, `jpg`, `svg`, `pdf` (default: `png`)
`scale`	`float`	Scale factor (default: `2.0`)

Running Tests

pytest tests/ -v

License

Available Tools

5 tools

export_assetsC

Export nodes as images (PNG, JPG, SVG, PDF).

ParametersJSON Schema

Name	Required	Default
`file_key`	Yes
`node_ids`	Yes
`format`	No	png
`scale`	No

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states 'Export nodes as images' without mentioning any side effects, such as whether files are saved locally, any destructive actions, rate limits, or authorization requirements. As a mutation tool, this lack of transparency is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one short sentence), but this is at the expense of providing necessary details. It could be improved without becoming overly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters (2 required), no output schema, and no annotations, the description is inadequate. It does not cover return value format, error cases, limitations (e.g., maximum node count), or any other contextual information needed for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no meaning to parameters beyond the formats listed in the purpose. It does not explain what file_key or node_ids are, nor the role of scale or available format values (despite enum not being used). The description fails to compensate for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Export' and the resource 'nodes', listing supported image formats (PNG, JPG, SVG, PDF). It distinguishes from sibling tools that focus on retrieving data or listing components/styles.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides no guidance on when to use this tool versus alternatives like get_frame_nodes or list_components. It does not mention prerequisites, contexts where other tools are more appropriate, or when export is not suitable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_figma_fileC

Get a complete Figma file by its key.

ParametersJSON Schema

Name	Required	Description	Default
`file_key`	Yes

TDQS

C2.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, and the description does not disclose behavioral traits such as authentication needs, response size, or safety. It only says 'get', implying a read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, very concise and front-loaded. It wastes no words, but could benefit from slight expansion for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and only one parameter, the description should explain what 'complete Figma file' entails (e.g., nodes, styles, assets). It lacks this context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions 'by its key' but does not explain what the key is, how to obtain it, or any constraints. With 0% schema coverage, the description fails to add meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves a complete Figma file using its key. It distinguishes from sibling tools which handle specific parts like exports or lists.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool over siblings or any prerequisites. The description only states the action without context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_frame_nodesC

Get specific nodes/frames from a Figma file.

ParametersJSON Schema

Name	Required	Description	Default
`file_key`	Yes
`node_ids`	Yes

TDQS

C2.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It only states 'get' without confirming read-only behavior, performance considerations, or error handling (e.g., invalid node_ids). The description adds no behavioral context beyond the verb.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. It is concise and front-loaded with the action, though it could benefit from slightly more detail without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and 2 required parameters, the description should hint at return values or typical use cases. It does not, leaving the agent unaware of what to expect after invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning parameter names have no descriptions. The description does not explain 'file_key' or 'node_ids', leaving their meanings inferred. It fails to add value over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets specific nodes/frames from a Figma file, using a specific verb and resource. However, it does not differentiate from sibling tools like 'get_figma_file' which retrieves the entire file, missing an opportunity to clarify scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as 'get_figma_file' for full file retrieval or 'export_assets' for asset extraction. The description lacks any context about appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_componentsB

List all components in a Figma file.

ParametersJSON Schema

Name	Required	Description	Default
`file_key`	Yes

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but provides no behavioral traits (e.g., read-only nature, auth needs, rate limits). It only states the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no wasted words, front-loaded and highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is too sparse. It omits return format, pagination, error handling, and any additional context needed for a complete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%; the description does not explain the file_key parameter. The schema provides a title, but the description adds no value beyond the parameter name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List all components in a Figma file' clearly states the verb (List), resource (components), and scope (in a Figma file), effectively distinguishing it from sibling tools like list_styles or get_figma_file.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., list_styles). The description lacks context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_stylesC

List all styles in a Figma file.

ParametersJSON Schema

Name	Required	Description	Default
`file_key`	Yes

TDQS

C2.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It only states 'List all styles', implying a read operation but fails to disclose any potential side effects, authentication needs, rate limits, or constraints like pagination. The behavior beyond listing is opaque.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no redundancy. However, it could be slightly expanded with necessary context without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (1 param, no output schema), the description is incomplete. It does not clarify what constitutes a style, whether pagination exists, or what the response format looks like, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the sole parameter 'file_key'. The phrase 'in a Figma file' hints at its purpose, but no details on what a file_key is or how to obtain it are provided, adding minimal value over the parameter name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List all styles in a Figma file' clearly specifies the action (list) and resource (styles), and the sibling tools (export_assets, get_figma_file, get_frame_nodes, list_components) are distinct, so the tool is well-differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus its siblings. There is no mention of alternatives or when not to use it, leaving the agent with minimal context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

5 tool updatesv0.1.0May 29, 2026
- First observedexport_assets
- First observedget_figma_file
- First observedget_frame_nodes
- First observedlist_components
- First observedlist_styles

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.2/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: exporting assets, retrieving full files, fetching specific nodes, listing components, and listing styles. No overlap or ambiguity.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (e.g., export_assets, get_figma_file, list_components), making naming predictable.

Tool Count4/5

5 tools is appropriate for a Figma-focused server, covering core read and export operations without being overwhelming or too sparse.

Completeness3/5

The set covers key read operations (file, nodes, components, styles) and asset export, but is missing file listing, search, and write operations, which are notable gaps for a full Figma API surface.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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