AppNiche MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct purpose: fetching app metadata, reviews, keyword difficulty, and app search. No overlap in functionality.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case (get_app_detail, get_app_reviews, get_keyword_difficulty, search_apps).
Tool Count4/5With 4 tools, the server is slightly minimal but remains well-scoped for its niche of iOS App Store data. Each tool adds clear value without unnecessary bloat.
Completeness4/5The set covers key app store operations: search, detail, reviews, and keyword analysis. Minor gaps like top charts or developer-level queries exist but don't impede core workflows.
Average 3.8/5 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 passing
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide safety info (readOnly, idempotent, non-destructive). Description adds no behavioral traits beyond the stated filters; e.g., no mention of pagination, sorting defaults, or rate limits.
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?
Single sentence, 16 words, no filler. Front-loaded with verb and resource. Efficiently conveys core purpose.
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?
Despite 11 parameters and no output schema, description omits crucial context like result format, pagination behavior, and sorting details. Schema coverage is low, leaving many parameters undocumented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 36%, but description lists only high-level filter dimensions (keyword, category, rating, etc.) without detailing specific parameters or constraints. Many parameters (offset, sort_by, sort_dir, min_*) are not addressed, insufficiently compensating for low coverage.
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?
Description clearly states verb (search and filter) and resource (iOS App Store apps) and lists many filter dimensions. Distinguishes well from siblings like get_app_detail and get_app_reviews.
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?
Implied usage for searching/filtering, but no explicit guidance on when to use this tool vs. siblings like get_app_detail or get_app_reviews. No when-not or alternative advice.
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 declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds context (iOS App Store scope) but does not disclose additional behavioral traits beyond the annotations. No contradictions.
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?
Single sentence, front-loaded with the key action 'Estimate difficulty and opportunity'. No redundant information or unnecessary detail. Every word earns its place.
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?
The description lacks explanation of the output (e.g., difficulty score range, opportunity metric). With no output schema, the agent cannot infer what the tool returns. The tool has 4 parameters and moderate complexity, so the description is insufficiently complete.
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 50% (2 of 4 parameters have schema descriptions). The description does not add meaning beyond the schema; it mentions 'country' and 'language' but no detail on values or defaults. Baseline is 3 for moderate coverage.
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 title 'Score an ASO keyword' and description 'Estimate difficulty and opportunity for one iOS App Store keyword in a country and language' clearly specify the verb (estimate), resource (keyword difficulty), and scope (iOS App Store, one keyword). It distinguishes itself from sibling tools like get_app_detail or search_apps.
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 keyword research on the iOS App Store, but does not explicitly state when to use this tool versus alternatives, nor does it provide conditions or exclusions. No guidance on when not to use or prerequisites is given.
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 declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that results include sentiment and topic signals, but does not elaborate on pagination, rate limits, or other behavioral traits beyond 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?
A single, front-loaded sentence that efficiently conveys the tool's purpose without wasted words.
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?
Tool is read-only with good annotations and sibling context. However, absence of output schema means the description should ideally hint at return structure; it mentions 'rows' with sentiment/topics but lacks specifics, which is a minor gap.
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 coverage is 67% with descriptions for limit and store_id. The description adds minimal value beyond the schema, only implying the app is identified by store_id. No additional context for parameters like limit or store.
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 verb 'Fetch' and the resource 'App Store review rows with sentiment and topic signals'. It distinguishes from sibling tools like get_app_detail (which returns app metadata) and get_keyword_difficulty (which deals with keywords).
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 fetching reviews of a single iOS app but does not explicitly state when to use this tool versus alternatives like get_app_detail or search_apps. Lacks when-not-to-use 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?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds that the tool returns metadata, ratings, and estimates, which is useful context beyond the annotations. No contradictions.
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?
Single sentence of 16 words, front-loaded with the core action. Every word earns its place, no redundancy.
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 tool with one parameter and no output schema, the description adequately outlines the return categories. However, it could be more explicit about the return structure or the nature of 'directional' estimates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It mentions 'app' but does not explain the required app_id parameter format or pattern. The agent needs to infer the identifier format from the schema pattern, which is not described.
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 it retrieves a single app profile with App Store metadata, ratings, and revenue/download estimates. This verb+resource combination distinguishes it from sibling tools like get_app_reviews (reviews) and search_apps (search).
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 implies use when needing detailed app data, and sibling names provide context, but there is no explicit guidance on when not to use this tool versus alternatives.
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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