mcp-server-comparedge

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by comparedge

Overview Schema Related Servers Score Discussions(1)

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Server Quality Checklist

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Latest release: v2.7.1
Disambiguation5/5
Each tool has a distinctly different purpose: comparing two tools, finding alternatives, getting leaderboards, retrieving pricing, getting tool profiles, listing categories, listing tools in a category, and searching. No overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using lowercase snake_case (e.g., compare_tools, get_alternatives, list_categories). No mixing of conventions.
Tool Count5/5
8 tools is an appropriate number for a server focused on software comparison and discovery. Each tool serves a clear and necessary function without redundancy or bloat.
Completeness5/5
The tool set covers the full user workflow: discovery (search, category listing, leaderboard), detailed information (profile, pricing), comparison, and alternatives. No obvious gaps for the stated domain.
Average 4.7/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on July 10, 2026
- 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.
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.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to 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.

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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It details what the tool returns (plans, prices, features, trial, free plan, link) and mentions extra for AI tools. Lacks info on data freshness or rate limits, but overall good.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with headings (BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES) and front-loaded purpose. Some example queries may be slightly redundant but overall concise for the detail provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description fully covers return values. Single parameter is well-documented. Usage guidelines and example queries provide rich context. Complete for the tool's complexity.
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 coverage is 100% and parameter description already explains slug transformation. Description adds context like 'use search_tools first if unsure', but does not add significant meaning beyond schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves pricing breakdown for a specific SaaS tool. It distinguishes from sibling tools like 'compare_tools' and 'get_tool' by specifying usage scenarios, e.g., 'use get_tool first if unsure whether the product exists'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit USAGE GUIDELINES section tells when to use (pricing queries), when not to use (use get_tool first for existence), and alternatives (compare_tools for comparison). Also includes example queries for clarity.
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?
Describes lookup by exact slug and output summary, but does not mention error handling for missing slugs or invalid inputs. Without annotations, this is the main gap.
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?
Well-structured with clear sections (BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES). Front-loaded with purpose and no unnecessary sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides good context on output and sibling tools, but lacks details on error cases or response format (no output schema). Adequate for most use cases.
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 covers slug parameter fully. Description adds example values and exact match behavior, but no additional semantics beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a full profile for a specific tool by slug, listing returned fields and distinguishing from sibling tools like get_pricing and get_alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides use cases (e.g., user asking about a tool), when to prefer alternatives, and example queries. Also advises using it to verify slug existence before other calls.
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?
No annotations provided, so description carries full burden. It describes behavior: fetches full profiles and presents parallel structure. Could add details like network calls or caching, but adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (overview, BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES). Each sentence adds value, though could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description details expected output (pricing plans, features, ratings). Sibling tools are present for context. Missing info like response structure but overall complete.
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?
Schema coverage is 100% with descriptions for both parameters. The description adds that slugs must be exact and suggests using search_tools first, providing context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a side-by-side structured comparison of two software products, specifying it returns pricing, features, ratings, and key differences. It effectively distinguishes from siblings like get_alternatives and get_pricing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (e.g., 'X vs Y' queries) and when not to use (e.g., get_pricing for full plan details, get_alternatives without specific second tool). Provides example queries and cautions about slug accuracy.
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 fully explains the scoring mechanism (against meaningful keywords, ignoring stopwords) and that it supports both exact names and natural language. It does not explicitly state it's read-only, but for a search tool this is implied. No side effects are mentioned, but the behavior is sufficiently transparent.
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 well-structured with sections, bullet points, and examples. It is concise (no unnecessary sentences) and front-loaded with the core purpose. Every sentence adds value, making it easy to read.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (search across 494+ products), no output schema, and sibling tools, the description covers purpose, usage, behavior, and examples. It lacks details on sorting order or pagination, but for a search tool this is acceptable. It is fairly complete overall.
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?
Schema coverage is 100% with both parameters described. The description adds significant value by explaining the query parameter accepts various types (name, keyword, use case) and provides examples. It also clarifies the limit default. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches software products by name, keyword, category, or natural language query, and specifies the returned fields. It distinguishes from siblings by mentioning its use before get_tool or get_pricing when the slug is uncertain, and differentiates from list_categories by supporting queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'USAGE GUIDELINES' section explicitly states when to use the tool: to discover tools when slug is unknown, before get_tool/get_pricing, and for category browsing. It also explains natural language query behavior. This provides clear guidance and context relative to siblings.
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?
No annotations exist, so description carries full burden. It discloses rating aggregation, ranking logic, and return fields. However, it lacks details on data freshness or update frequency, which would enhance transparency.
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?
Description is well-structured into sections (intro, BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES). Every sentence is informative and the length is appropriate for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 2 optional parameters, the description fully explains return fields, behavior, and interconnections with sibling tools. It provides complete guidance for an agent to invoke correctly.
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?
Schema covers 100% of parameters with descriptions. The description adds value by clarifying usage context (e.g., use list_categories for slug, default values) and linking to sibling tools, but does not introduce new parameter-level semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets top-rated tools by category with aggregated scores, listing specific return fields. It distinguishes itself from siblings like list_category (all vs top N) and compare_tools (comparison vs ranking).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (user asks for best/top-rated) and when-not-to-use (use list_category for all tools). Suggests prior use of list_categories and combination with get_pricing. Includes example queries for clarity.
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?
No annotations provided, so description carries full burden. It describes behavior: returns ranked list with specific fields, sorting by rating or price, filtering free_only. It does not mention pagination or rate limits, but those are not critical for this tool.
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?
Well-structured with sections (BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES). Front-loaded with main purpose. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains what each entry includes (name, rating, free plan, price, link). Covers all aspects needed: sorting, filtering, example queries, and sibling tool combinations.
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?
Schema coverage is 100%, and description adds additional context: explains sort_by options ('rating' vs 'startingPrice') and free_only filter. It also provides the category slug hint referencing list_categories.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all verified SaaS tools in a specific category with pricing, ratings, and free plan status. It distinguishes from siblings like get_leaderboard (top 10 only) and list_categories (list categories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage examples and when to use vs alternatives: 'Use list_categories first if you are unsure of the correct category slug' and 'Combine with get_leaderboard when the user wants only the top-rated tools'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes behavior: filters same category, excludes reference product, returns top results by rating, includes markdown link. With no annotations, it carries full burden and does so thoroughly.
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?
Well-structured with sections: purpose, BEHAVIOR, USAGE GUIDELINES, EXAMPLE QUERIES. Front-loaded, concise, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-param tool with no output schema, description fully explains return values (name, price, free plan, rating, link) and usage context. Complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100% but description adds default limit (5) and max (10), and clarifies slug is the tool to find alternatives for. Adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds top verified alternatives to a given software tool within the same category, sorted by rating, and lists return fields. It distinguishes from siblings like compare_tools and get_leaderboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use guidance with example queries like 'what are alternatives to X?'. Suggests combining with get_pricing for cost comparison. No ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully discloses the tool's behavior: returns a complete index of all categories, each entry includes slug and display name. No side effects as it's a read-only operation. Complete transparency.
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?
Concise yet comprehensive. Structured with summary, BEHAVIOR, USAGE GUIDELINES, and EXAMPLE QUERIES. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 0 params, no output schema, and low complexity, the description fully satisfies completeness by detailing the return structure and usage context with examples.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has zero parameters with 100% schema coverage. The description explicitly confirms 'No parameters required', adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all 44 supported software categories with slugs and display names. It uses a specific verb-resource combination and implicitly distinguishes from siblings like list_category and search_tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use (first to get slug before other calls) and for browsing. Also states no parameters required. Provides clear usage context without ambiguity.
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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