my-image-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: checking config status, setting up config, generating images, and editing images. There is no overlap between the configuration tools and the image operation tools, and the descriptions make the boundaries obvious.
Naming Consistency4/5Most tools follow a verb_noun pattern (setup_image_api, generate_image, edit_image), but image_config_status deviates by using a noun_noun format. The inconsistency is minor and does not hinder readability.
Tool Count5/5With only 4 tools, the server is well-scoped for its purpose. Each tool is necessary and there is no bloat or redundancy, making the set easy to navigate.
Completeness5/5The server covers the full lifecycle of image generation and editing, including configuration setup and status checks. There are no obvious gaps for its stated domain, as generation and editing are the core operations.
Average 4.1/5 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 is failing
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a write operation (readOnlyHint false). The description adds a helpful behavioral detail about dimension inference when size is omitted, but it does not disclose external API dependencies or failure modes.
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 concise sentences: the first states the core purpose, the second gives a useful refinement about size inference. No extraneous detail.
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 9 parameters and an output schema, the description is brief but sufficient when combined with structured fields. However, it lacks context about the configured API and relationship to sibling configuration tools.
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 56%, and the description only restates the size inference behavior already documented in the schema. It adds no new meaning for parameters like quality, background, outputFormat, or outputCompression that lack descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Generate one or more images', a specific verb and resource, and clearly distinguishes from siblings like edit_image and setup_image_api by focusing on the generation action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no explicit when-to-use or alternative guidance, though the purpose implicitly separates it from edit and setup tools. The mention of the 'configured OpenAI-compatible Images API' provides context but no exclusions or fallback instructions.
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?
Annotations already disclose the tool is not read-only, not idempotent, and not destructive. The description adds minimal behavioral context: that it operates via an 'OpenAI-compatible Images API' and supports 1–16 input images. It doesn't mention side effects like API costs, or clarify state changes, but with annotations present, the bar is lower. A score of 3 is appropriate because it adds some context but not rich behavioral detail.
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, tightly written sentence that front-loads the core action and scope. Every word adds value, and there is no fluff or repetition of schema details. It is an excellent example of concise, well-structured documentation for a tool with complex parameters.
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?
Given the tool has 11 parameters and an output schema, the description is appropriately high-level. It mentions the input images count, the operation types, and the configured API, which covers the prerequisites (setup_image_api). The output schema handles return values. No critical context like licensing or requirements seems missing, so a 4 is merited.
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 64%, so the schema carries most parameter semantics. The description does not explicitly describe any parameters, but it does reinforce the meaning of 'prompt' and 'images' by stating 'Edit, combine, or mask one to sixteen input images', which aligns with the images parameter. It adds no new information about other parameters like size, quality, or delivery, so the baseline 3 is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb ('Edit, combine, or mask') and clearly identifies the resource ('one to sixteen input images') and the backend ('configured OpenAI-compatible Images API'). This distinguishes it from the sibling tools, especially generate_image, by focusing on modifying existing images rather than creating new ones.
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 clearly implies use cases: editing, combining, or masking input images. It doesn't explicitly name alternatives or state 'when not to use', but the phrasing makes it evident that this is for working with existing images, not generating from scratch. Since guidelines are implied rather than directly contrasted with siblings, it earns a 4, not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds a key behavioral guarantee: 'This tool never returns the API Key.' This is valuable security-relevant context beyond the structured fields.
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 sentences, no unnecessary words. The first sentence states the purpose, the second adds a critical safety guarantee. Every word 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 status check with an output schema and comprehensive annotations, the description is adequate. It covers the essential behavior (checking configuration) and adds the notable security constraint. No further detail is required.
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?
With zero parameters, the schema coverage is vacuously 100%, and the rubric assigns a baseline of 4 for no params. The description adds nothing about parameters, which is appropriate since there are none to describe.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description "Check whether the image API is configured" uses a specific verb and resource, clearly distinguishing this status-check tool from the sibling setup, generate, and edit tools. It unambiguously states what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for verifying configuration status but does not explicitly state when to use it over siblings or provide exclusions. There is no mention of alternatives, so usage guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare idempotent and non-destructive, and not read-only. The description adds critical behavioral detail: the secret is submitted locally and never passed as a tool argument, which is a security-relevant trait. It also notes the page is localhost. No contradiction with annotations.
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 just two sentences, with the first sentence front-loaded with the core purpose. The second sentence adds a crucial security detail without any fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter setup tool, the description fully covers what the tool does, where it operates (localhost), and the security model. An output schema exists, so return values need not be explained. It is complete for the tool's simplicity and the annotations provided.
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 tool has zero parameters and an empty schema, so schema coverage is 100%. With no parameters to describe, the baseline of 4 applies, and the description contains no parameter info because none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Create a one-time localhost setup page for Base URL and API Key.' It clearly distinguishes from sibling tools like generate_image and edit_image, which are about image operations, and image_config_status, which likely checks status. The purpose is unambiguous.
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 clear context: it is a one-time localhost setup page, implying it should be used before image operations. However, it does not explicitly name alternatives or state when not to use this tool. The security note adds context for when it is appropriate, but no explicit exclusion is provided.
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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