@mcp/openverse

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes: get_image_details, get_image_stats, get_related_images, and search_images are clearly differentiated. However, search_images and search_images_for_essay have overlapping functionality, as the latter seems like a specialized version of the former, which could cause minor confusion for an agent.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_image_details, search_images). There are no deviations in naming conventions, making the set predictable and easy to parse.
Tool Count5/5
With 5 tools, the count is well-scoped for an image search and retrieval server. Each tool serves a specific function in the domain, and there are no extraneous or redundant tools, making the set appropriately sized.
Completeness4/5
The tool surface covers core operations for image search and retrieval, including search, details, stats, and related images. A minor gap exists in lacking explicit tools for actions like filtering or advanced search parameters, but agents can likely work around this using the provided search tools.
Average 2.9/5 across 5 of 5 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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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.
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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 this is a read operation ('Get'), but doesn't mention permissions, rate limits, error handling, or what 'detailed information' includes. This is inadequate for a 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 with no wasted words. It's appropriately sized and front-loaded, clearly stating the tool's purpose 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' entails, potential response formats, or error cases. For a tool with no structured output documentation, this leaves significant gaps for 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 100%, so the schema already documents the 'image_id' parameter as an Openverse image ID in UUID format. The description adds no additional meaning beyond what the schema provides, such as examples or context for obtaining the ID, meeting the baseline for high 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 verb ('Get') and resource ('detailed information about a specific image'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_image_stats' or 'get_related_images' which might also provide image information, so it 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. It doesn't mention when to choose this over 'get_image_stats' for statistics or 'search_images' for broader queries, nor does it specify prerequisites like needing an image ID.
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 but only states the basic action. It doesn't cover aspects like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what the return format might be (e.g., list of images with metadata). This leaves significant gaps for a tool that likely queries an external API.
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. It's front-loaded and efficiently conveys the core purpose without unnecessary elaboration, making it easy for an agent 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 what 'related' means (e.g., by content, tags, or metadata), the format of returned images, or any behavioral traits like pagination details. For a tool with three parameters and likely API interactions, 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so parameters like 'image_id', 'page', and 'page_size' are well-documented in the schema. The description adds no additional semantic context beyond implying that 'image_id' is used to find related images, which is already clear from the schema. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'images related to a specific image', making the purpose understandable. However, it doesn't distinguish this tool from its siblings like 'get_image_details' or 'search_images', which might also retrieve images, so it misses full differentiation.
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 'search_images' or 'get_image_details'. It lacks any context about use cases, prerequisites, or exclusions, leaving the agent to 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. While 'Search' implies a read-only operation, the description doesn't mention important behavioral aspects like rate limits, authentication requirements, pagination behavior beyond the parameters, error conditions, or what the response format looks like. This leaves significant gaps for an agent to understand how to interact with this tool effectively.
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 immediately communicates the core functionality without any wasted words. It's appropriately sized for a search tool and gets straight to the point with no 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?
For a search tool with 11 parameters and no output schema, the description is insufficient. It doesn't explain what the search results look like, how pagination works beyond the parameters, what licensing 'openly-licensed' specifically means, or how mature content filtering behaves. With no annotations and no output schema, the agent lacks crucial information about the tool's behavior and results.
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 100%, with all 11 parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions, so it meets the baseline expectation but doesn't provide extra value. The description doesn't explain relationships between parameters or provide usage examples.
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 ('Search for') and resource ('openly-licensed images on Openverse'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling 'search_images_for_essay', which appears to serve a similar search function with potentially different parameters or use cases.
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 'search_images_for_essay' or other sibling tools. There's no mention of prerequisites, typical use cases, or limitations that would help an agent choose between available options.
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 mentions 'suitable for illustrating an essay,' hinting at relevance filtering, but does not detail how suitability is determined, what the output format is, or any limitations like rate limits or authentication needs. For a search tool with zero annotation coverage, this is insufficient to guide the agent fully.
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: 'Search for images suitable for illustrating an essay.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence contributes directly to understanding the tool's intent.
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 (4 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, output format, and usage guidelines. While the schema covers parameters well, the description does not address gaps in understanding how the tool behaves or what results to expect, making it inadequate for full contextual 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 all parameters thoroughly. The description does not add any additional meaning beyond what the schema provides, such as explaining how 'essay_topic' and 'concepts' interact or what 'suitable' entails. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not 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 tool's purpose: 'Search for images suitable for illustrating an essay.' It specifies the verb 'search' and the resource 'images,' with the context of 'illustrating an essay' providing additional clarity. However, it does not explicitly differentiate from sibling tools like 'search_images,' which might be more general, leaving room for ambiguity.
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 mentions the context of 'illustrating an essay,' but does not specify prerequisites, exclusions, or when to choose this over sibling tools such as 'search_images' or 'get_related_images.' This lack of explicit usage instructions reduces its effectiveness for an AI agent.
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 mentions 'Get statistics,' implying a read-only operation, but doesn't specify details like whether it requires authentication, has rate limits, returns aggregated data, or handles errors. This leaves significant gaps in understanding 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, clear sentence that directly states the tool's function without any wasted words. It's front-loaded and efficiently communicates the essential information, making it easy to parse and understand 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 for a tool that likely returns statistical data. It doesn't explain what specific statistics are provided (e.g., counts by provider, trends), the format of the output, or any prerequisites, leaving the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so there's no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a high score for not adding unnecessary complexity.
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 with a specific verb ('Get') and resource ('statistics about image providers and counts'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_image_details' or 'search_images', which might provide overlapping or related functionality, so it misses 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 such as 'get_image_details' and 'search_images' available, there's no indication of whether this tool is for high-level summaries, specific queries, or other contexts, leaving usage ambiguous.
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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