The ComparEdge MCP server lets you research, compare, and discover 495+ SaaS and AI software tools — including verified pricing, features, ratings, and alternatives — without an API key.
Search for tools (search_tools): Find software by name, keyword, category, or natural language query (e.g., "best CRM for startups"), returning up to 20 results.
Get a tool profile (get_tool): Retrieve a full overview of a specific product using its slug, including description, category, rating, free plan status, starting price, and key features.
Get pricing details (get_pricing): Access complete, verified pricing breakdowns — all plans, costs per tier, free trial/plan availability, and per-token pricing for AI/LLM tools.
Compare two tools (compare_tools): Side-by-side structured comparison of two products covering pricing, features, ratings, and key differences.
Compare pricing (compare_pricing): Focused plan-by-plan cost comparison between two tools with value assessment.
Find alternatives (get_alternatives): Discover top-rated alternatives to a given tool within the same category, sorted by rating, with comparison links.
Browse by category (list_category): List all tools in a specific category, sortable by rating or starting price, with optional free-plan filtering.
View leaderboards (get_leaderboard): See the top-rated tools in any category or overall, ranked by aggregated G2 and Capterra scores.
List all categories (list_categories): Explore all 45 supported software categories with their slugs and display names.
Enables retrieval of pricing, ratings, and alternative tools for GitHub Copilot, an AI code completion service.
Offers pricing and rating data for Google's AI products and services, such as Gemini.
Delivers information on Meta's AI models, including pricing and user ratings.
Allows querying pricing plans, ratings, and feature breakdowns for Notion, a versatile productivity tool.
Provides comprehensive data on OpenAI's models, including token pricing and ratings for GPT-4 and other offerings.
Your assistant already knows what Notion is. It does not know that Notion Plus costs $12 a seat this month, or that the tool you are evaluating quietly dropped its free plan in spring. Training data ages; prices move. This server closes that gap with verified pricing, plans, ratings and alternatives for 494 SaaS and AI tools, checked against vendor pages before they ship. Live docs and examples: comparedge.com/mcp.
Zero dependencies, no API key, no account. Works in Claude Desktop, Cursor, VS Code and any other MCP client.
Add one block to your client config:
{
"mcpServers": {
"comparedge": {
"command": "npx",
"args": ["-y", "@comparedge/mcp-server@latest"]
}
}
}Claude Desktop keeps this file at ~/Library/Application Support/Claude/claude_desktop_config.json. Cursor: Settings, then MCP, then Add Server. VS Code with Copilot reads .vscode/mcp.json. Per-client walkthroughs live in the setup guide.
Related MCP server: StackSwap
Once connected, questions like these stop producing guesses and start producing verified numbers:
How much does Slack cost for a team of 40 on annual billing?
Find me a CRM under $20 per user that still has a real free plan.
I want to leave Salesforce. What do people switch to, and what does the move cost?
Which AI coding assistants are top rated right now?
Compare Notion and Coda plan by plan.
Eight tools, each a read-only lookup against the catalog.
Tool | Returns | Params |
| products matching a name, keyword or use case |
|
| full profile for one product |
|
| every plan with price, period and features, plus trial and free-plan status |
|
| two products side by side: pricing, features, ratings |
|
| top alternatives in the same category, ranked by rating |
|
| all tools in one category with a pricing overview |
|
| top-rated tools, one category or overall |
|
| all 44 category slugs with display names | none |
Products are addressed by slug: notion, github-copilot, screaming-frog. When in doubt, search_tools first. Category slugs double as public pages a human can open, for example the LLM category hub. LLM entries carry per-token API pricing on top of the plan data.
Four workflows ship as prompts your client can expose as slash commands:
Prompt | Args | What it runs |
|
| searches the catalog, prices the top matches, returns a ranked pick |
|
| plan-by-plan price comparison |
|
| profile, verified pricing and top alternatives in one pass |
|
| category leaderboard with pricing for the leaders |
accounting ai-agents ai-assistants ai-coding ai-image ai-meeting ai-productivity ai-security ai-video ai-voice ai-writing analytics cloud-hosting cloud-security compliance crm crypto-analytics crypto-exchanges crypto-portfolio-trackers crypto-tax crypto-telegram-bots crypto-trading-bots crypto-wallets customer-support data-observability databases defi-tools design-tools dex email-marketing endpoint-security erp finops hr-tools iam llm password-managers payments project-management seo-tools vector-databases video-conferencing vpn website-builders
The catalog is maintained by ComparEdge. Every price traces to the vendor's own pricing page, harvested from the live DOM and re-verified on a rolling schedule; each record carries its verification date. The pipeline is documented in the methodology, and the full catalog ships as an open dataset under CC BY 4.0. If a tool is not a fit, the alternatives hub covers switch paths for the whole catalog.
MIT. Built on the Model Context Protocol.
Side-by-side structured comparison of two software products. Returns pricing, features, ratings, and key differences for each tool.
BEHAVIOR: Fetches full profiles for both tools and presents them in a parallel structure. Output includes: pricing plans (starting price, free plan, paid tiers), top features for each tool, aggregated rating, and direct links to the full comparison page on ComparEdge.
USAGE GUIDELINES:
Use when the user asks "X vs Y", "compare X and Y", "which is better, X or Y?", or "what is the difference between X and Y?".
Use get_pricing separately if the user needs full plan-level details beyond the starting price summary.
Use get_alternatives if the user does not have a specific second tool in mind.
Slugs must be exact. Use search_tools first if unsure.
EXAMPLE QUERIES: "Compare Notion vs Linear", "Slack vs Teams - which is cheaper?", "What is the difference between Jira and Asana?", "HubSpot vs Salesforce pricing"
| Name | Required | Description | Default |
|---|---|---|---|
| tool1 | Yes | Slug of the first tool to compare | |
| tool2 | Yes | Slug of the second tool to compare |
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.
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.
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.
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.
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.
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.
Find the top verified alternatives to a given software tool within the same category, sorted by rating. Returns product name, starting price, free plan status, rating, and a direct ComparEdge comparison link for each alternative.
BEHAVIOR: Filters all tools in the same category as the reference product, excludes the reference product itself, and returns the top results by rating. Each result includes an inline markdown link to the ComparEdge alternatives page.
USAGE GUIDELINES:
Use when the user asks "what are alternatives to X?", "what can I use instead of X?", or "X is too expensive, what else is there?".
Combine with get_pricing to compare costs across alternatives.
Set limit to control how many alternatives to return (default 5, max 10).
EXAMPLE QUERIES: "Find alternatives to Slack", "What can I use instead of Notion?", "Cheaper alternatives to Salesforce"
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Slug of the tool to find alternatives for | |
| limit | No | Maximum number of alternatives to return (default: 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.
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.
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.
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.
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.
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.
Get top-rated software tools by category, ranked by aggregated G2 and Capterra scores. Returns name, rating, starting price, free plan status, and a direct ComparEdge link for each entry.
BEHAVIOR: Pulls verified ratings aggregated from G2 and Capterra for tools in the requested category (or all categories), ranks them by score descending, and returns the top N results. Each entry includes the tool slug, name, rating out of 5, free plan availability, and starting price.
USAGE GUIDELINES:
Use when the user asks "what is the best X tool?", "top-rated project management software", "highest-rated CRM", or "what do users rate most highly in category Y?".
Use list_categories first to find the correct category slug if unsure.
Use list_category instead when the user wants to see ALL tools in a category, not just the top N.
Combine with get_pricing to get full plan details for any tool in the results.
EXAMPLE QUERIES: "What is the best CRM tool?", "Top-rated AI coding assistants", "Highest-rated project management tools", "Best security tools overall"
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of top tools to return (default: 10) | |
| category | No | Category slug to filter by, or "all" for overall leaderboard (default: "all") |
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.
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.
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.
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.
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.
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.
Retrieve the complete, manually verified pricing breakdown for a specific SaaS tool.
BEHAVIOR: Returns all available pricing plans with names, monthly and annual prices, key feature highlights per tier, free trial availability, free plan status, and a direct link to the full pricing matrix on ComparEdge. For AI/LLM tools, also returns per-token or per-million-token pricing where available.
USAGE GUIDELINES:
Use this tool when the user asks "how much does X cost?", "what are the pricing plans for X?", "does X have a free tier?", or "what is the cheapest plan for X?"
Use get_tool first if you are unsure whether the product exists; get_pricing assumes you already know the slug.
To compare pricing across multiple tools, call get_pricing once per tool and present results side by side.
Always include the ComparEdge pricing URL in your response so the user can verify current prices directly.
EXAMPLE QUERIES: "What are the pricing plans for Linear?", "Does Notion have a free plan?", "How much does HubSpot CRM cost per seat?", "What is the cheapest project management tool under $10/month?"
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | URL-safe product identifier. Convert product name to lowercase, replace spaces with hyphens (e.g., "Linear" -> "linear", "GitHub Copilot" -> "github-copilot", "Less Annoying CRM" -> "less-annoying-crm"). Use search_tools first if unsure of the exact slug. |
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.
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.
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.
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.
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.
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.
Retrieve the full profile for a specific software tool by its slug identifier. Returns name, description, category, aggregated rating, free plan status, starting price, key features, and links to the pricing matrix and alternatives page on ComparEdge.
BEHAVIOR: Looks up the tool by exact slug. Returns a structured profile with all available metadata. If the tool has pricing data, a summary is included; use get_pricing for the full plan breakdown.
USAGE GUIDELINES:
Use when the user asks "what is X?", "tell me about X", or "give me an overview of X".
Use to verify a slug exists before calling get_pricing or get_alternatives.
Prefer get_pricing when the user specifically asks about cost or plans.
EXAMPLE QUERIES: "Tell me about Linear", "What does Notion do?", "Give me an overview of HubSpot"
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Tool slug identifier (e.g., "openai", "notion", "github-copilot") |
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.
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.
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.
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.
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.
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.
List all 44 supported software categories with their slugs and display names.
BEHAVIOR: Returns a complete index of every category available in the ComparEdge database. Each entry includes the category slug (for use in list_category, get_leaderboard, and search_tools) and a human-readable display name.
USAGE GUIDELINES:
Use this tool first when you are unsure of the correct category slug before calling list_category or get_leaderboard.
Use to help the user browse what types of software are covered.
No parameters required.
EXAMPLE QUERIES: "What categories of software does ComparEdge cover?", "What SaaS categories are available?", "I want to find CRM tools - what is the slug?", "Show me all software categories"
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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.
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.
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.
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.
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.
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.
List all verified SaaS tools in a specific software category with pricing overview, ratings, and free plan status.
BEHAVIOR: Returns a ranked list of all tools in the requested category. Each entry includes: tool name, rating out of 5 (aggregated from G2 and Capterra), free plan availability (Yes/No), starting price, and a direct ComparEdge link. Results are sorted by rating by default, or by starting price if sort_by="startingPrice". Use free_only=true to filter to tools with a free plan.
USAGE GUIDELINES:
Use when the user asks "what are the best CRM tools?", "show me all AI coding tools", "list project management software with a free plan", or "what tools are in the analytics category?".
Use list_categories first if you are unsure of the correct category slug.
Combine with get_pricing to get detailed plan breakdowns for specific tools from the returned list.
Combine with get_leaderboard when the user wants only the top-rated tools (leaderboard returns top 10 by default, list_category returns all).
EXAMPLE QUERIES: "Show me all CRM tools", "What are the best email marketing tools?", "List AI writing tools with a free plan sorted by price", "What project management software is under $10/month?"
| Name | Required | Description | Default |
|---|---|---|---|
| sort_by | No | Sort field: "rating" (default, highest rated first) or "startingPrice" (lowest price first) | |
| category | Yes | Category slug (e.g., "llm", "ai-coding", "crm"). Use list_categories to get all valid slugs. | |
| free_only | No | If true, return only tools that offer a free plan (default: false) |
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.
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.
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.
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.
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.
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.
Search 494+ software products by name, keyword, category, or natural language query. Returns name, category, rating, free plan availability, starting price, and ComparEdge URL.
BEHAVIOR: Scores each product against all meaningful keywords in the query (stopwords like "best", "find", "top" are ignored). Supports both exact product names and natural language queries.
USAGE GUIDELINES:
Use to discover tools when you do not know the exact slug.
Use before calling get_tool or get_pricing if the slug is uncertain.
Use for category browsing: query "crm", "ai coding", "project management".
Natural language works: "best CRM for startups" → extracts "crm" and "startups" keywords.
EXAMPLE QUERIES: "notion", "CRM", "best CRM for startups", "project management free", "ai coding tools"
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default: 5) | |
| query | Yes | Search query string (product name, keyword, or use case) |
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.
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.
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.
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.
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.
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v2.5.7list_category3 fields changedInput schema / properties / category / descriptionPrevious value: -"Category slug (e.g., \"llm\", \"ai-coding\", \"crm\")"New value: +"Category slug (e.g., \"llm\", \"ai-coding\", \"crm\"). Use list_categories to get all valid slugs."Input schema / properties / free_only / descriptionPrevious value: -"If true, return only tools with a free plan (default: false)"New value: +"If true, return only tools that offer a free plan (default: false)"Input schema / properties / sort_by / descriptionPrevious value: -"Sort field: \"rating\" (default) or \"startingPrice\""New value: +"Sort field: \"rating\" (default, highest rated first) or \"startingPrice\" (lowest price first)"v2.5.5get_pricing1 field changedInput schema / properties / slug / descriptionPrevious value: -"Tool slug identifier"New value: +"URL-safe product identifier. Convert product name to lowercase, replace spaces with hyphens (e.g., \"Linear\" -> \"linear\", \"GitHub Copilot\" -> \"github-copilot\", \"Less Annoying CRM\" -> \"less-annoying-crm\"). Use search_tools first if unsure of the exact slug."v2.1.5compare_toolsget_alternativesget_leaderboardget_pricingget_toollist_categorieslist_categorysearch_toolsEach 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.
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.
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.
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.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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