poster-design-mcp
Server Quality Checklist
Latest release: v1.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: discovering templates, learning design principles, creating a single poster, and creating variants. Even the two create tools are distinguishable by single vs. batch behavior.
Naming Consistency5/5All tool names follow the same verb_noun snake_case pattern: list_, get_, create_, create_. The naming is predictable and indicates the action and resource clearly.
Tool Count5/5Four tools is well-scoped for a poster design server, covering discovery, guidance, creation, and variation. The set feels intentionally minimal rather than bloated or incomplete.
Completeness4/5The core workflow is covered: browse templates, learn design rules, create a poster, and generate variants. Minor gaps exist around modifying or deleting generated posters, but these are not clearly required for the server's stated purpose.
Average 3.6/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It does transparently mention file output formats, the output directory, and the return value, and it adds design automation traits such as auto-fitted display type and protected legibility. However, it does not mention overwrite behavior, permissions, or other side effects beyond writing the poster file.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: purpose, key output behavior, and return value appear in three short sentences. The design-behavior clause is useful but uses some jargon (e.g., 'band structure', 'protected legibility') that is not explained; still, there is minimal waste.
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 complexity (16 parameters, nested content objects, four templates), the description is brief but the schema compensates with rich parameter documentation. It covers the output path and basic design behavior, but it lacks guidance on when to choose this tool over create_poster_variants and does not summarize template requirements in the main description.
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?
Schema description coverage is high (88%), and the schema already documents parameter meanings, defaults, enums, and nested template-specific fields. The description adds no parameter-level detail beyond general design intent, so the baseline 3 applies because the schema carries most of the semantic weight.
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 states a specific action ('Render a business poster to a PNG/JPG'), a target location ('~/Poster Designs'), and the return value ('Returns the file path'). It clearly identifies this as a poster-generation tool, though it does not explicitly distinguish it from the sibling create_poster_variants.
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?
No guidance is given on when to use this tool versus create_poster_variants, or how it relates to list_poster_templates and get_design_principles. Usage context is only implied by the phrase 'Render a business poster' and the parameter schema; there are no exclusions or alternative-selection hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It accurately communicates the key batch behavior (several variants in one call) and the comparison intent, but it does not mention return format, failure modes, or any side effects. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence that delivers the core value proposition without wasted words. It is front-loaded with the batch concept and ends with the purpose, making it easy to scan. Slightly more explicit structure would improve it, but it is appropriately sized.
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?
For a 3-parameter tool with nested objects and no output schema, the description gives enough context to select the tool and understand its general purpose. However, an agent would still need to rely on the schema for override semantics and would not know what the response contains. Functional for selection, incomplete for full invocation confidence.
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?
Schema description coverage is 100%, so the structured schema already documents content, template fallback behavior, and variant overrides. The description adds the conceptual 'same message across templates' framing but no additional parameter-level detail beyond what the schema provides.
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 conveys that the tool generates the same message across multiple templates/palettes in a single call, which differentiates it from the singular create_poster sibling. It lacks an explicit verb but the resource and batch scope are unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'to compare directions' provides a clear context for when this tool is appropriate: when the user wants to explore multiple visual directions at once. It does not explicitly name alternatives or exclusions, but the batch comparison purpose is evident from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It communicates that this is a read-oriented informational tool returning rules, type scale, and ratios, but it does not explicitly state the return format, side effects, or any constraints such as whether brandColor changes the returned rules.
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?
Two short sentences with no filler. The first sentence establishes what the tool returns and the second gives actionable usage guidance, so every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with two optional parameters and no output schema, the description names the key return content and intended use. It would be more complete with a sentence about what the response contains, but for this complexity the coverage is adequate.
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?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds no parameter-level meaning, but the baseline of 3 applies because the schema handles the heavy lifting.
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 identifies the resource as the generator's design rules, type scale, and layout ratios, and states its intended use in writing or critiquing copy. It does not explicitly contrast with sibling tools, but the subject matter is obviously distinct from template listing and poster creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence gives explicit use cases: 'For writing copy that fits, or critiquing output.' It does not state exclusions or point to alternatives, so it stops short of a 5, but the situational context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It implies read-only behavior through 'field guide' and describes the optional filter behavior ('Pass a template id for that one layout only'), which adds useful context. However, it never explicitly states that the operation is read-only, nor does it describe the default return behavior when no template is passed.
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?
Three short sentences with no fluff. The purpose is front-loaded, the optional parameter behavior is stated in the second sentence, and the workflow guidance is in the third. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description adequately covers what the tool returns, the filtering behavior, and when to call it. The main gap is the absence of any distinction from the sibling get_design_principles, which could leave an agent uncertain which reference tool to select.
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?
Schema description coverage is 100%, so the schema already documents the template parameter. The description adds only 'for that one layout only,' which reinforces the schema's 'Just this layout, in full' but does not materially extend it. This is the appropriate baseline when the schema handles parameter documentation.
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 identifies the tool as a reference for poster layouts, palettes, sizes, and fonts, which is a specific resource and content scope. It does not explicitly use the verb 'list' but the name and 'field guide' make the informational purpose clear. It distinguishes itself from create_poster by placement in workflow, though it does not differentiate from sibling get_design_principles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit contextual guidance: 'Call once before create_poster if unsure.' This tells the agent when to use the tool and provides a workflow cue. It does not state when not to use it or explicitly compare to get_design_principles, so it stops short of full alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/suprisedr/poster-design-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server