Figma MCP Tool

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but there is some overlap between 'export_multiple_images' and 'get_node_images' that could cause confusion. The descriptions help differentiate them, but the boundaries are not perfectly clear.
Naming Consistency4/5
The naming follows a consistent verb_noun pattern with minor deviations, such as 'export_multiple_images' using an adjective. Overall, the pattern is readable and predictable across the tool set.
Tool Count5/5
With 7 tools, the count is well-scoped for a Figma integration server. Each tool appears to serve a specific purpose related to extracting or retrieving design assets and data.
Completeness4/5
The tool set covers key operations for accessing Figma assets and styles, but there are minor gaps such as updating or modifying nodes. Agents can likely work around these limitations for most common workflows.
Average 2.8/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

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 implies a read operation ('get') but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or what 'all image resources' entails (e.g., format, size, pagination). This is a significant gap for a tool with no annotation coverage.
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 in Chinese, front-loaded with the core purpose. It has no wasted words, though it could benefit from more detail given the lack of annotations and sibling tools.
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 complexity (1 parameter, no annotations, no output schema, and multiple sibling tools), the description is incomplete. It doesn't clarify the 'node' context, differentiate from siblings, or explain return values, leaving gaps for the agent to understand when and how to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'url' documented as 'Figma文件URL，必须包含node-id参数' (Figma file URL, must include node-id parameter). The description adds no meaning beyond this, as it doesn't explain the 'node' context or provide additional syntax details. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '获取节点中的所有图片资源' (Get all image resources in a node) states a clear verb ('get') and resource ('image resources in a node'), but it's vague about what 'node' means in context (e.g., Figma node). It doesn't distinguish from siblings like 'get_figma_image' or 'export_multiple_images', leaving ambiguity about scope or output format.
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 alternatives. With siblings like 'get_figma_image' and 'export_multiple_images', the description lacks any context, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('获取' - get) without mentioning permissions, rate limits, output format, or whether it's a read-only operation. For a tool with no annotations, this leaves critical behavioral traits unspecified.
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 ('获取节点的SVG数据') with no wasted words. It's appropriately sized for a simple tool, though it could be more front-loaded with additional context to improve clarity without sacrificing brevity.
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 annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'node' refers to (e.g., Figma design node), the format of the SVG data returned, or any error conditions. For a tool in a context with multiple sibling tools, more detail is needed to guide proper use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter semantics beyond what the input schema provides. With 100% schema description coverage, the schema already documents the single parameter 'url' as 'Figma文件URL，必须包含node-id参数' (Figma file URL, must include node-id parameter). The baseline score of 3 reflects adequate coverage by the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '获取节点的SVG数据' (Get node SVG data) states a clear verb ('获取' - get) and resource ('节点的SVG数据' - node SVG data), but it's vague about what type of node and from what system. It doesn't differentiate from siblings like 'get_node_images' or 'extract_node_elements', leaving ambiguity about scope and specificity.
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 alternatives. Given siblings like 'get_node_images' and 'extract_node_elements', the description lacks any context about use cases, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool exports images but doesn't describe what 'export' entails (e.g., file generation, download links, permissions required, rate limits, or side effects). For a tool that likely creates outputs, this lack of detail is a significant gap in transparency.
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?
The description is a single, efficient sentence in Chinese that directly states the tool's function without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place.
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 complexity (export operation with multiple parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., image URLs, file paths, error handling) or behavioral aspects like permissions or side effects. For a tool with potential side effects, this leaves critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all four parameters (fileId, nodeIds, format, scale). The description adds no additional parameter semantics beyond what's in the schema. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate or enhance understanding.
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 action ('批量导出' - batch export) and resource ('多个节点的图片' - multiple node images), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'get_node_images' or 'get_node_svg', which might have overlapping functionality. The purpose is clear but lacks sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get_node_images' or 'get_node_svg'. There's no mention of prerequisites, context, or exclusions. The agent must infer usage from the name and parameters alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what the tool does (extract elements) but lacks behavioral details such as permissions required, rate limits, output format, or whether it's a read-only operation. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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?
The description is a single, efficient sentence in Chinese that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the purpose.
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 annotations and no output schema, the description is incomplete for a tool with 2 parameters. It explains what the tool does but lacks critical context like behavioral traits, output details, or usage scenarios. For a tool in this context, more information is needed to fully guide an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters ('url' and 'includeDetails'). The description adds no additional meaning beyond what's in the schema, such as examples or context for parameter usage. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.
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 action ('提取' meaning 'extract') and the target ('节点中的所有设计元素' meaning 'all design elements in a node'), specifying the resource types (images, vectors, components). It distinguishes from siblings like 'get_node_images' (only images) and 'get_node_svg' (only SVG), but doesn't explicitly name these alternatives. This makes the purpose specific but not fully 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 alternatives like 'get_node_images' or 'get_node_svg'. The description implies it extracts all element types, but doesn't state when to prefer this comprehensive extraction over more specific tools. There are no exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions fetching images based on a Figma URL but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what the output looks like (e.g., image data, URLs, or metadata). For a tool that likely involves external API calls, this 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Chinese that directly states the tool's function without any unnecessary words. It's front-loaded and appropriately sized for its purpose, making it easy to parse quickly.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain the return values (e.g., image bytes, download links, or error formats), which is crucial for a tool that fetches images. For a tool with three parameters and likely external dependencies, more context is needed to ensure proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting all three parameters (url, format, scale) with details like required status, defaults, and constraints. The description doesn't add any meaningful semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage.
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 '根据Figma URL获取节点的图片' clearly states the action (获取/获取) and resource (节点的图片), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_node_images' or 'get_node_svg', which appear to have similar functions, so it doesn't reach the highest score.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get_node_images' or 'get_node_svg'. It lacks context about specific use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves style data but doesn't cover important aspects like authentication needs, rate limits, error handling, or what specific style data is returned (e.g., colors, typography). This leaves significant gaps for an agent to understand the tool's behavior.
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?
The description is a single, efficient sentence in Chinese that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded with the core functionality.
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 complexity of retrieving style data from Figma, no annotations, and no output schema, the description is incomplete. It doesn't explain what '样式数据' (style data) includes, how results are structured, or any behavioral traits like permissions or limitations, making it inadequate for full agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('url' and 'generateCSS') thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as URL format examples or CSS generation details, meeting the baseline for high schema coverage.
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's purpose as '获取节点的样式数据' (get node style data) from a Figma URL, which is a specific verb+resource combination. However, it doesn't explicitly differentiate this from sibling tools like 'get_node_svg' or 'extract_node_elements', which might also retrieve node-related data but in different formats.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_node_svg' for SVG data or 'get_figma_image' for images, nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('获取基本信息'), without mentioning any traits like whether it's read-only, requires authentication, has rate limits, or what the output format might be. This is a significant gap for a tool with no annotation coverage.
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?
The description is a single, efficient sentence in Chinese that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'basic information' includes (e.g., metadata, structure, or other details), leaving gaps in understanding the tool's behavior and output, which is inadequate for a tool with no structured data support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what the input schema provides. With schema description coverage at 100% (the 'url' parameter is documented as 'Figma文件URL'), the baseline score of 3 is appropriate, as the schema does the heavy lifting without additional value from the description.
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 action ('获取' meaning 'get') and resource ('Figma文件的基本信息' meaning 'basic information of Figma file'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_figma_image' or 'get_figma_styles', which also retrieve Figma-related information, so it doesn't reach the highest score.
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?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_figma_image' and 'get_figma_styles' available, there's no indication of what distinguishes this tool (e.g., that it retrieves general metadata vs. specific assets or styles), leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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