mcp-searchapi

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct search vertical (general web, news, shopping, jobs, academic, maps, videos, Amazon). The descriptions clearly specify when to use each, leaving no ambiguity between them.
Naming Consistency4/5
Most tools follow a 'google_<service>' pattern, but youtube_search and amazon_search use a '<service>_search' pattern, creating a minor inconsistency. The overall style is still readable and predictable.
Tool Count5/5
With 8 tools, the server is well-scoped for a search aggregation service. Each tool covers a major search category without unnecessary redundancy.
Completeness5/5
The tool surface covers a broad range of search needs: general web, news, shopping, jobs, academic, maps, videos, and e-commerce. For a search-focused server, this is a comprehensive set with no obvious missing core capabilities.
Average 4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral disclosure burden. It only says 'Search' without revealing any behavioral traits such as whether the operation is read-only, how pagination behaves, rate limits, or the format of returned results. For a mutating side-effect free search tool this is a modest gap, but without annotations it is a clear shortfall.
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 two sentences, tightly written, and front-loaded: the first sentence states the action, the second adds usage context. Every sentence contributes, and there is no redundant phrasing or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters, no output schema, and no annotations. The description clearly communicates purpose and usage but omits any explanation of return values, pagination, or configuration behavior. For a simple search tool this is functionally adequate, but it leaves room for more contextual guidance, hence a 3 rather than a higher score.
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?
The schema provides 100% coverage for all five parameters, each with a description, so the baseline is 3. The tool description itself adds no parameter-level meaning (it doesn't reference query, num, or limit), but since the schema already documents them, no penalty is warranted.
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 opens with a specific verb+resource: 'Search Google Scholar for academic papers, citations and authors.' This clearly distinguishes it from sibling search tools like google_search or google_news by narrowing the domain to academic content and explicitly naming the resource. The mention of 'peer-reviewed sources' further reinforces its unique niche.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence, 'Use this for research questions where peer-reviewed sources matter,' gives clear guidance on when to employ the tool. It lacks explicit alternatives or when-not-to-use instructions, though the sibling context (e.g., google_search) makes the comparison implicit. Thus it earns a 4, not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states what is searched and returned, but does not mention localization effects (despite location parameter), pagination, result limits, price currency, or potential variability in availability/ratings. This is a significant transparency 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?
The description is two sentences with no filler. The first sentence front-loads the core action ('Search Google Shopping for products with prices, sellers and ratings') and the second adds a clear use case. Every word earns its place.
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?
No output schema exists, so the description should hint at return content; 'products with prices, sellers and ratings' does that. However, it omits important behavioral context like pagination, result limits, and localization effects that the schema documents but the description does not reinforce. For a straightforward search tool it is mostly complete, but lacks edge-case disclosure.
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% with detailed descriptions for all 7 parameters, so the baseline is 3. The tool description adds no additional meaning beyond the schema, but the schema already does a solid job, so a mid score 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 verb 'Search' and resource 'Google Shopping', and specifies the returned data: 'products with prices, sellers and ratings'. It also differentiates from siblings by saying 'Use this for price comparison and product availability questions', which is distinct from generic Google 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'Use this for price comparison and product availability questions'. However, it does not mention when not to use the tool or name alternative tools, so it lacks full exclusion guidance.
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?
No annotations are provided, so the description carries the full burden. It adds some behavioral context by listing product attributes returned (price, rating, review count, ASIN), but does not explicitly state read-only semantics, pagination, or potential response structure. The word 'Search' suggests read-only, but more disclosure would be better.
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?
Two concise sentences, front-loaded with purpose. The second sentence reinforces the Amazon-specific use case, adding relevance for sibling differentiation without redundancy.
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?
The description provides purpose and some output field details, while the schema covers all parameters with clear descriptions. There is no output schema, so the returned fields hint helps. Minor gaps like response envelope or error handling are typical for a search tool, but it is sufficiently complete for an agent to select and invoke.
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?
The input schema provides 100% coverage with descriptions for all four parameters, including defaults and constraints. The description adds no parameter-level meaning beyond the schema, so the baseline of 3 applies.
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 Amazon for products and lists key output fields (price, rating, review count, ASIN). It distinguishes from siblings by explicitly targeting Amazon, which differentiates it from google_shopping and other general 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It says 'Use this for e-commerce product lookups on Amazon specifically', providing clear context for when to use. However, it does not explicitly name alternatives or state exclusion cases, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the basic function and usage recommendation without covering result format, pagination behavior, rate limits, or any other nuances. This is a significant gap for a tool with no annotation support.
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 two sentences long, front-loading the primary action and immediately following with clear usage guidance. There is zero redundancy or fluff, making it highly efficient.
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?
For a search tool with seven parameters, a required query, and no output schema, the description provides essential context: what it does and when to prefer it. The schema covers all parameters, and the recency emphasis clarifies the key distinction from siblings. It could mention result ordering or limitations, but it remains complete enough for an agent to select and invoke it correctly.
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 description coverage is 100%, so all seven parameters are already well-documented in the schema. The description itself adds no parameter-specific insights, keeping the score at the baseline of 3 per the calibration guidance.
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 it searches Google News for recent news articles, giving a specific verb and resource. The mention of 'recent' and 'what is happening with a topic' distinguishes it from general google_search and other sibling tools, leaving no ambiguity about scope.
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 description provides explicit usage guidance: 'Use this instead of google_search when recency matters or the user asks what is happening with a topic.' It names the alternative and gives concrete conditions, which exceeds minimal expectations and directly aids tool selection.
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?
With no annotations, the description carries the burden of behavioral disclosure. It does add useful information by specifying 'organic web results' (excluding ads) and general scope, but it does not discuss pagination, result format, or any limitations. It provides some context beyond a simple tautology, so a 3 is appropriate.
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 a single, well-structured sentence that front-loads the action and clearly states the purpose. It is concise and avoids unnecessary detail, making it easy for an agent to parse quickly.
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?
For a simple search tool with 7 well-documented parameters and no output schema, the description covers the core purpose and usage guidance. It does not explicitly mention return value details, but the schema covers parameters and the primary behavior is clear. It is complete enough for basic selection and invocation.
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 description coverage is 100% – all 7 parameters have detailed descriptions in the input schema. The tool description itself adds no parameter-level information, so the baseline of 3 applies. It neither improves nor detracts from the schema's clarity.
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 'Search Google and return organic web results' – a specific verb plus resource. It also distinguishes itself from sibling tools like google_news, google_shopping, and google_scholar by emphasizing 'organic web results' and listing use cases (general questions, current events, fact-checking, authoritative pages).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this for general questions, current events, fact-checking, and finding authoritative pages on any topic.' This gives clear context for when to use the tool, though it does not explicitly mention exclusions or name alternative tools. The sibling list implies specialized alternatives, so it earns a 4.
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?
No annotations are provided, so the description carries the burden of disclosure. It does state the result attributes (channel, duration, view count, publish date), giving some behavioral context. However, it does not explicitly state that this is a read-only operation or mention any rate limits, pagination, or result ordering, leaving some gaps.
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 two sentences long, with the first stating the action and outcome and the second giving when-to-use guidance. Every word earns its place; there is no redundancy or fluff.
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?
With 4 parameters and no output schema, the description provides a reasonable overview of what the tool returns (channel, duration, view count, publish date) and when to use it. Minor details like result ordering and pagination are not mentioned, but the schema covers limits and the core purpose is clear.
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%, with each parameter already well described in the input schema. The description does not add extra parameter-level detail; it only paraphrases the query purpose and result fields. Therefore, the baseline of 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's function: 'Search YouTube for videos with channel, duration, view count and publish date.' It specifies the resource (YouTube) and the scope (videos) with key result attributes, distinguishing it from sibling search tools like google_search or google_news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage context: 'Use this when the user wants video content, tutorials or talks.' It does not mention when not to use or name alternative tools, but the context is clear enough to guide selection among the listed 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?
With no annotations provided, the description carries the transparency burden. It discloses that results include addresses, ratings, hours, and coordinates, and that the tool is for location-bound queries, which implies a read-only search behavior. It does not mention pagination, rate limits, or localization nuances, but the schema covers those details.
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 two sentences, front-loaded with the core purpose and immediately followed by usage guidance. No wasted words.
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?
With no output schema, the description compensates by enumerating the return data (addresses, ratings, hours, coordinates). It also mentions the typical use cases, though it doesn't cover all param nuances; those are in the schema, so the overall picture is solid.
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?
All six parameters have thorough schema descriptions (100% coverage), so the baseline is 3. The main description adds no additional parameter semantics beyond the schema, though the example query in the schema ('coffee shops in Athlone') is echoed in the description's 'location-bound question'.
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 uses the verb 'Search' with the resource 'Google Maps for places and local businesses', and lists specific output data (addresses, ratings, hours, coordinates). This clearly distinguishes it from sibling search tools like google_news or google_shopping, which target other content types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states 'Use this for "near me", "where can I", or any location-bound question,' giving clear context for when to invoke the tool. However, it does not name alternative tools for non-location queries or state explicit exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states a limitation ('does not accept a country code') and explains how to geo-target via the 'location' parameter. This adds meaningful behavior beyond what the schema alone provides, though it doesn't cover every edge like pagination specifics.
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 three sentences long, each earning its place: the first defines what the tool does, the second specifies when to use it, and the third gives a critical usage constraint. It is front-loaded and contains zero filler.
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?
For a search tool with no output schema and five parameters, the description is sufficiently complete. It covers the core purpose, usage context, and a key behavioral limitation. The parameter nuances are already well-handled by the schema, so the description doesn't need to repeat them.
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?
The schema covers all parameters with clear descriptions (100% coverage), so the baseline is 3. The description adds extra value by explaining how to use 'location' for geo-targeting and advising to include the place in the query as well as in 'location' for best results. This enriches the schema's 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's function: 'Search Google Jobs for job listings with company, location and apply links.' It uses a specific verb and resource, and explicitly differentiates it from generic search siblings by saying 'Use this for any hiring, vacancy or job market question.' This leaves no ambiguity about the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this for any hiring, vacancy or job market question.' It also gives a key exclusion: 'This engine does not accept a country code,' and recommends passing 'location' for geo-targeting. While it doesn't name alternative tools, the guidance is clear and actionable.
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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