Excalidraw MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific actions on drawings: creation, deletion, retrieval, listing, updating, and three distinct export formats. There is no overlap or ambiguity between tools, making it easy for an agent to select the correct one.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., create_drawing, delete_drawing) with no deviations. The naming is predictable and readable throughout the set, enhancing usability and coherence.
Tool Count5/5
With 8 tools, the server is well-scoped for managing Excalidraw drawings, covering core CRUD operations and multiple export options. Each tool earns its place without feeling excessive or insufficient for the domain.
Completeness5/5
The tool set provides complete CRUD/lifecycle coverage for drawings (create, get, list, update, delete) and includes essential export functionalities (JSON, PNG, SVG). There are no obvious gaps, ensuring agents can handle all typical workflows without dead ends.
Average 2.9/5 across 8 of 8 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
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Create') but does not mention permissions, side effects, or response format. This is inadequate for a mutation tool, as it omits critical behavioral details like what happens on success or failure.
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 with no wasted words, making it easy to parse. It is appropriately sized and front-loaded, earning full marks for 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 complexity of a creation tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, behavioral traits, and expected outcomes, making it insufficient for effective tool 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%, so the description must compensate by explaining parameters. It adds no meaning beyond the schema, failing to clarify what 'name' and 'content' represent (e.g., drawing title vs. Excalidraw JSON data). This leaves parameters undocumented and reduces usability.
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 verb ('Create') and resource ('new Excalidraw drawing'), making the purpose evident. However, it does not distinguish this tool from its sibling 'update_drawing' in terms of when to create versus update, which prevents a perfect 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 'update_drawing' or prerequisites for creation. It lacks explicit instructions on usage context or exclusions, leaving the agent with minimal direction.
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 states the action ('Export') but does not describe what this entails—e.g., whether it's a read-only operation, if it requires specific permissions, what the output looks like, or any side effects. The description is minimal and lacks context beyond 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?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a simple tool, with zero waste or redundancy.
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's simplicity (1 parameter, no annotations, no output schema), the description is incomplete. It lacks details on parameter meaning, behavioral traits (e.g., read-only vs. destructive), and output format, which are essential for an agent to use it correctly. The description does not compensate for the absence of structured data.
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 input schema has one parameter (id) with 0% description coverage, and the tool description does not mention parameters at all. It adds no meaning beyond what the schema provides (e.g., explaining what 'id' refers to, such as a drawing identifier). With low schema coverage, the description fails to compensate, leaving parameters undocumented.
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 ('Export') and target resource ('an Excalidraw drawing to JSON'), making the purpose understandable. It distinguishes from siblings like export_to_png and export_to_svg by specifying the output format as JSON, but does not explicitly differentiate from other export or drawing-related tools beyond 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an existing drawing ID), exclusions, or comparisons to siblings like get_drawing (which might retrieve drawing data) or other export tools. Usage is implied only by the tool name and description.
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 states the tool retrieves a drawing by ID but does not describe what happens if the ID is invalid (e.g., error handling), whether it requires authentication, rate limits, or the format of the returned drawing. For a read operation with zero annotation coverage, this leaves significant gaps in understanding 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 that front-loads the core action ('Get an Excalidraw drawing by ID') with zero wasted words. It is appropriately sized for a simple retrieval tool and earns its place by clearly stating 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 the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It lacks details on error cases, return format (e.g., drawing data structure), and how it differs from siblings like 'export_to_json'. For a tool in a set with multiple export options, more context is needed to guide effective use.
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%, so the description must compensate. It mentions the 'id' parameter but provides no additional meaning beyond what the schema implies (a string of minLength 1). It does not explain what the ID represents (e.g., a unique identifier for drawings), where to obtain it, or format examples. The description adds minimal value over the bare 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 the verb ('Get') and resource ('an Excalidraw drawing'), specifying retrieval by ID. It distinguishes from siblings like 'list_drawings' (which retrieves multiple) and 'create_drawing' (which creates new), but could be more explicit about the distinction. The purpose is specific and actionable.
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 does not mention prerequisites (e.g., needing a valid drawing ID), exclusions (e.g., not for creating or updating), or direct comparisons to siblings like 'list_drawings' for bulk retrieval. Usage is implied but not explicitly stated.
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 states 'List all Excalidraw drawings', which implies a read-only operation, but does not clarify if it's paginated (implied by parameters), what the output format is, or any rate limits or permissions required. This leaves significant gaps in understanding tool 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, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose without unnecessary elaboration, earning full marks for brevity and structure.
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 a list operation with pagination parameters, no annotations, and no output schema, the description is incomplete. It does not explain the pagination behavior, return format, or any constraints, making it inadequate for the agent to fully understand how to use the tool effectively.
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?
With 2 parameters and 0% schema description coverage, the schema provides no descriptions for 'page' and 'perPage'. The tool description does not mention or explain these parameters at all, failing to compensate for the lack of schema documentation and leaving their purpose unclear to the agent.
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 ('List') and resource ('all Excalidraw drawings'), making the purpose evident. However, it does not differentiate from potential siblings like 'get_drawing' (which might fetch a single drawing) or 'export_to_json' (which might list in a specific format), leaving room for improvement in 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. With siblings like 'get_drawing' (for a single drawing) and export tools, it lacks explicit instructions on usage context, prerequisites, or exclusions, offering minimal help for agent decision-making.
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 full burden for behavioral disclosure. It states 'Update' which implies mutation, but doesn't specify permissions required, whether changes are reversible, rate limits, or what happens on success/failure. This is inadequate for a mutation tool with zero 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 that gets straight to the point with zero wasted words. It's appropriately sized for a simple update operation and front-loads the essential information.
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?
For a mutation tool with no annotations, no output schema, and 2 undocumented parameters, the description is insufficient. It doesn't explain what 'content' should contain, what happens after update, or error conditions. The context signals indicate significant gaps that aren't addressed.
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%, so the description must compensate. It mentions 'by ID' which hints at the 'id' parameter, but doesn't explain what 'content' represents or its format. With 2 undocumented parameters, the description adds minimal value beyond what's implied by the tool name.
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 ('Update') and resource ('Excalidraw drawing by ID'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'create_drawing' or 'get_drawing' beyond the basic verb difference, which prevents a perfect 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 'create_drawing' for new drawings or 'get_drawing' for retrieval. There's no mention of prerequisites (e.g., needing an existing drawing ID) or exclusions, leaving usage context unclear.
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 a drawing but does not cover critical aspects such as whether it requires specific permissions, if it modifies the original drawing, rate limits, or what the output looks like (e.g., file format details). This is a significant gap for a tool with mutation-like 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 with zero waste. It is front-loaded and appropriately sized for the tool's purpose, making it easy to understand at a glance without unnecessary elaboration.
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 (5 parameters, no output schema, no annotations), the description is incomplete. It does not address behavioral traits, parameter meanings, or output details, leaving gaps that could hinder an AI agent's ability to use the tool correctly. For an export tool with multiple configurable options, more context is needed.
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 the input schema, which has 0% description coverage. It does not explain what 'id', 'quality', 'scale', etc., mean or how they affect the export. However, with 5 parameters including defaults and ranges in the schema, the baseline is 3 as the schema provides some structure, but the description fails to compensate for the lack of semantic details.
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 ('Export') and the resource ('an Excalidraw drawing'), specifying the output format ('to PNG'). It distinguishes from sibling tools like 'export_to_json' and 'export_to_svg' by naming the format, but does not clarify if it's for a single drawing or batch, which could improve 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 like 'export_to_svg' or 'export_to_json'. It does not mention prerequisites (e.g., needing an existing drawing) or exclusions, leaving usage context implied but not explicit.
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 full burden for behavioral disclosure. It states the action ('Export') but doesn't describe what happens during export (e.g., whether it modifies the drawing, requires specific permissions, has rate limits, or returns the SVG as data or a file). For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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 with zero wasted words. It's appropriately sized for a simple export tool and front-loads the core action. 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 tool's moderate complexity (export operation), no annotations, no output schema, and 1 undocumented parameter, the description is insufficient. It doesn't explain what the export produces (e.g., SVG string, file download), error conditions, or how it differs from sibling export tools. The agent lacks critical context for 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 doesn't mention any parameters, while the schema has 1 parameter (id) with 0% description coverage. The description doesn't compensate by explaining what 'id' represents (e.g., drawing identifier). However, with only 1 parameter, the baseline is 4, but the lack of any parameter context in the description reduces this to 3.
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 verb ('Export') and resource ('an Excalidraw drawing to SVG'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like export_to_json or export_to_png, which perform similar export operations to 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 like export_to_json or export_to_png. It doesn't mention any prerequisites, context for choosing SVG format, or exclusions. The agent must infer usage from the tool name 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 action is 'Delete', implying a destructive mutation, but does not disclose critical traits like whether deletion is permanent, requires specific permissions, or has side effects (e.g., affecting associated files). This leaves significant gaps for a destructive operation.
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, front-loaded sentence with zero waste—'Delete an Excalidraw drawing by ID'—directly conveying the core action and parameter. It is appropriately sized and efficiently structured.
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's complexity (destructive mutation with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It fails to address behavioral risks, return values, or error conditions, making it inadequate for safe and effective use by 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?
The schema description coverage is 0%, but the description adds meaning by specifying that the 'id' parameter refers to 'an Excalidraw drawing by ID', clarifying its purpose. However, it does not provide details on ID format, source, or validation, which limits compensation for the low schema coverage.
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 clearly states the specific action ('Delete') and target resource ('an Excalidraw drawing by ID'), distinguishing it from sibling tools like 'get_drawing', 'update_drawing', or 'create_drawing'. It precisely communicates the tool's function without redundancy.
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, such as whether it's irreversible or if there are prerequisites like confirming deletion. It lacks explicit context for usage compared to siblings like 'update_drawing' or 'list_drawings'.
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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