Marp MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: generate_slide creates individual slide content, init_presentation sets up a new project structure, and list_slide_layouts provides information about available layouts. There is no overlap or ambiguity between these three functions.
Naming Consistency5/5All tools follow a consistent verb_noun naming pattern (generate_slide, init_presentation, list_slide_layouts) with clear, descriptive names that indicate their specific actions. The naming convention is uniform throughout the set.
Tool Count3/5With only 3 tools, this server feels somewhat thin for a presentation creation domain. While the tools cover core functions, additional operations like editing slides, managing themes, or exporting presentations would enhance completeness. The count is borderline but reasonable for a minimal implementation.
Completeness3/5The tools cover initialization, layout listing, and slide generation, which are foundational for a presentation workflow. However, there are notable gaps: no tools for updating or deleting slides, managing presentation metadata, or exporting to formats like PDF or HTML. This limits the agent's ability to handle full presentation lifecycles.
Average 3/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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 tool generates a slide and returns a markdown string, but lacks details on permissions, side effects, error handling, or rate limits. For a tool with mutation implications (generating content), this is insufficient, as it doesn't cover critical behavioral traits beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action and output. It avoids unnecessary words and directly communicates the tool's function without redundancy, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (with nested objects in parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain the return format in detail (e.g., structure of the markdown), error cases, or how to handle the 'params' object effectively. This leaves significant gaps for an AI agent to use the tool correctly in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters ('layoutType' and 'params'). The description adds minimal value by implying the use of 'academic theme layouts' and specifying the output as a markdown string, but doesn't elaborate on parameter usage beyond what the schema provides. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate a slide') and resource ('academic theme layouts'), with a specific output format ('markdown string for copy-paste'). It distinguishes from sibling tools like 'init_presentation' and 'list_slide_layouts' by focusing on slide creation rather than presentation initialization or layout listing. However, it doesn't explicitly differentiate from potential overlapping functions, keeping it at 4 instead of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 mentions 'academic theme layouts' but doesn't explain when to choose this over other tools or contexts, such as when to use 'init_presentation' first or how it relates to 'list_slide_layouts'. This lack of explicit usage context or exclusions results in a minimal score.
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 'Initialize' which implies a creation/mutation operation, but doesn't specify permissions needed, whether it overwrites existing directories, or any side effects like file generation details. This leaves significant gaps in understanding the tool's behavior 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action and resources without any wasted words. It's appropriately sized for the tool's purpose, making it easy to grasp quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (initializing a project with multiple components) and the lack of annotations and output schema, the description is incomplete. It doesn't cover what the tool returns, error conditions, or detailed behavioral traits, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting all 5 parameters. The description adds no additional meaning beyond what's in the schema, such as explaining relationships between parameters or usage examples. Since schema coverage is high, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Initialize a new Marp presentation project') and the resources involved ('directory structure, theme, and templates'), which is specific and informative. However, it doesn't explicitly differentiate from sibling tools like 'generate_slide' or 'list_slide_layouts', which might handle slide creation or layout listing rather than project initialization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'generate_slide' or 'list_slide_layouts'. It lacks context on prerequisites, such as whether this is for starting a new project from scratch, or any exclusions, like not using it for modifying existing presentations.
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 the tool lists layouts but doesn't disclose behavioral traits such as whether it's a read-only operation, if it requires authentication, rate limits, or how the data is returned (e.g., format, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose ('List all available slide layouts') and adds useful detail ('with their parameters and descriptions'). There is zero waste, and every word earns its place by clarifying the scope of the listing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is adequate but has clear gaps. It covers the purpose but lacks behavioral context (e.g., read-only nature, return format) and usage guidelines. Without annotations or output schema, the description should do more to inform the agent about how the tool behaves and when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for 0 parameters, as the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'slide layouts', specifying what information is included ('parameters and descriptions'). It distinguishes from sibling tools like 'generate_slide' (creation) and 'init_presentation' (initialization) by focusing on listing existing layouts. However, it doesn't explicitly differentiate from potential similar listing tools (though none exist in siblings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 prerequisites, context for usage, or exclusions. For example, it doesn't clarify if this should be used before generating slides or if it's for reference only, leaving the agent to infer usage from the purpose alone.
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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