semantic-image-search-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct function: semantic search, metadata retrieval, index maintenance, and archive statistics. There is no overlap or ambiguity between them.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with lowercase and underscores: search_images, get_image_info, reindex_archive, get_archive_stats. The verbs are imperative and the nouns are clear.
Tool Count5/5Four tools is a well-scoped set for a semantic image search server, covering the essential operations without unnecessary bloat. It fits perfectly within the typical 3-15 tool range.
Completeness4/5The tool set covers search, metadata retrieval, reindexing, and archive stats, which are the core workflows for this domain. A minor gap is the lack of direct image file access or delete/index management, but these are not critical for search functionality.
Average 4.6/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 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.
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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
- Behavior4/5
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 does disclose the return structure including a success flag, and implies the archive must already be indexed. However, it does not explicitly state that the operation is non-mutating, nor does it mention any potential side effects. Still, the detailed return list provides useful transparency about what the tool yields.
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 well-structured and appropriately sized. It opens with a one-sentence purpose, adds a brief contextual overview, then lists the return fields in a clean bulleted format. Every part serves a purpose, and the return field list is essential given the lack of an output schema. It is front-loaded with the most important information first.
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?
Given that the tool has no parameters and no output schema, the description fully compensates by enumerating all return fields with their meanings. It also clarifies the scope ('indexed photo archive') and provides enough context to understand what the tool does and returns. For a simple stats query, this is complete.
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, so the input schema is empty. Per the rubric, a 0-parameter tool gets a baseline of 4. The description does not need to add parameter semantics, and it appropriately focuses on the output. No parameter documentation is required.
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 begins with a clear statement: 'Get statistics about the indexed photo archive.' It specifies the resource (photo archive) and the action (get statistics), and lists the specific types of statistics (total count, date range, storage size, distribution by camera and folder). This clearly distinguishes it from sibling tools like search_images (searching) and get_image_info (single image details).
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 when to use this tool: when you need an overview of the entire photo archive. It states it 'Provides an overview of your photo collection'. However, it does not explicitly mention alternatives or exclusions (e.g., 'for details on a single image, use get_image_info'), so it lacks explicit when-not guidance.
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?
With no annotations, the description carries the full burden of transparency. It discloses the return structure in detail, including a success flag and optional fields (e.g., gps if available), giving a good sense of the operation's output. It does not explicitly state the operation is read-only or describe error conditions, but the 'get' verb and success flag imply a safe, well-defined behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by structured Args and Returns sections. Although it lists many metadata fields, this is necessary because there is no output schema to document the return value, so every detail 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?
Without an output schema or annotations, the description must be self-sufficient, and it is. It covers input semantics, return format comprehensively, and notes optional availability of certain fields. The absence of explicit error handling is mitigated by the success flag, making it complete for a simple get-by-id tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines image_id as a required string with no description (0% coverage). The description compensates by explaining that it is a 'Unique identifier for the image (obtained from search results)' and clarifies how it is used to fetch the metadata, adding crucial meaning beyond the schema.
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 a specific verb 'Get' and resource 'detailed metadata for a specific image', then enumerates metadata categories (EXIF, camera settings, location, file details). This clearly distinguishes it from siblings like search_images, which finds images.
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 provides clear context by stating that image_id is 'obtained from search results', implying usage after a search. However, it does not explicitly mention when not to use this tool or name alternative tools such as get_archive_stats, leaving room for ambiguity.
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?
With no annotations provided, the description carries the full burden. It explains the scanning behavior, the impact of force (full re-index, slow), and the return dictionary with success, counts, and errors. It does not mention side effects like index overwriting or permissions, but for this tool the disclosed details are adequate.
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 well-structured: a one-sentence summary, a clarifying paragraph, then Args and Returns sections. It is front-loaded and contains no fluff or redundant information. Every sentence contributes to understanding the tool's purpose, usage, and behavior.
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 tool with one parameter, no annotations, and no output schema, this description is thorough. It explains what the tool does, when to run it, the meaning of the only parameter, and the shape of the return value. The agent has enough information to select and invoke it correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only a boolean 'force' with a default, but the description adds meaningful semantics: 'If True, re-index ALL images (slow). If False, only index new or modified images (default, recommended).' This compensates for the 0% schema description coverage and clarifies the parameter's effect and performance trade-off.
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 clearly states the tool's function: 'Re-index the photo archive for new or modified images.' The verb 're-index' and resource 'photo archive' are specific. It distinguishes itself from sibling tools like search_images and get_archive_stats, which serve different purposes (querying and stats).
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 provides clear context: 'This should be run after adding new photos to the archive.' It also recommends the default behavior (force=False) as the preferred approach. It does not explicitly name alternatives or exclusion cases, but the context is sufficient given the distinct sibling tool purposes.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals key traits: AI-powered semantic search based on visual content rather than filenames/tags, and details the return structure including success, query, count, and results. No contradictions exist.
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 well-organized with a clear overview, Args section with bullet points, and Returns section. Every sentence adds value, and the format is front-loaded with the core purpose. It is appropriately sized for the complexity of the tool.
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 search tool with five parameters, no annotations, and no output schema, the description is exceptionally complete. It explains the search semantics, every parameter with examples, and the return value structure, leaving no critical gaps for an agent to invoke and interpret the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides zero description coverage, so the description must explain all parameters. It does so thoroughly, including examples for query ('person in a room'), defaults for limit, date format expectations, and a folder_pattern example. This fully compensates for the lack of schema documentation.
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 clearly states 'Search images using natural language queries with optional filters' and further explains it performs semantic search across the photo archive. This specific verb+resource formulation distinguishes it from sibling tools like get_image_info and reindex_archive, which address different operations.
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 conveys a clear use case: finding images by visual content using natural language. It doesn't explicitly mention when not to use it or point to alternatives, but the context is unambiguous enough for an agent to select it appropriately among the given siblings.
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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