Google News MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: decode_google_news_url handles URL conversion, list_categories provides metadata, and the five feed tools (get_category_feed, get_geo_feed, get_search_feed, get_top_headlines, get_topic_feed) target different news retrieval methods. The descriptions reinforce these boundaries, making tool selection unambiguous.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case: decode_google_news_url, get_category_feed, get_geo_feed, get_search_feed, get_top_headlines, get_topic_feed, and list_categories. The naming is predictable and readable throughout the set, with 'get_' for retrieval actions and 'list_'/'decode_' for other operations.
Tool Count5/5
With 7 tools, the count is well-scoped for a news server. It covers core functionalities like URL decoding, category listing, and multiple feed types (category, geo, search, headlines, topic), each earning its place without being excessive or sparse. This aligns with typical MCP server tool counts of 3-15.
Completeness4/5
The tool set provides comprehensive coverage for news retrieval and processing, including decoding, listing categories, and fetching feeds by various criteria. A minor gap exists in lacking update/delete operations for saved feeds or preferences, but this is reasonable for a read-only news domain, and agents can work around it with external state management.
Average 3.7/5 across 7 of 7 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 carries full burden. It mentions the tool 'gets news' but doesn't disclose behavioral traits like rate limits, authentication requirements, pagination behavior, error conditions, or whether this is a read-only operation. The description is minimal beyond the basic function.
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?
The description is appropriately sized with clear sections (purpose, args, returns). The first sentence states the core purpose, followed by parameter documentation and return format. No wasted sentences, though the structure could be more front-loaded with usage context.
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?
Given 3 parameters with 0% schema coverage and no annotations, the description provides basic parameter semantics and return format. However, with an output schema available, the return value documentation is redundant. For a news retrieval tool with geographic filtering, more context about data freshness, source limitations, or result formatting would be helpful.
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 0%, so the description must compensate. It provides basic semantics for all 3 parameters (location, language, country) with examples for location and default values for language/country. However, it doesn't specify format requirements, valid country/language codes, or constraints beyond the basic definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get news specific to a geographic location' which is a specific verb+resource combination. It distinguishes from siblings like get_category_feed, get_search_feed, and get_topic_feed by specifying geographic focus. However, it doesn't explicitly contrast with get_top_headlines which might also have geographic filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like get_category_feed, get_search_feed, and get_top_headlines available, there's no indication of when geographic filtering is preferred over category-based, search-based, or top headlines approaches.
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 carries the full burden. It mentions that parameters default to config values, which is useful context, but fails to disclose critical behavioral traits such as rate limits, authentication needs, error handling, or pagination. For a tool fetching external data, this omission is significant.
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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value without redundancy, making it easy to parse and front-loaded with essential information. No wasted words.
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?
Given the tool's moderate complexity (2 parameters, no annotations, but an output schema exists), the description is partially complete. It covers parameters well and the output schema handles return values, but it lacks behavioral context (e.g., rate limits) and usage guidelines, leaving gaps for effective agent operation.
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?
With 0% schema description coverage, the description compensates well by explaining both parameters: 'language' and 'country' with examples (e.g., 'en', 'US') and noting defaults ('from config'). This adds meaningful semantics beyond the bare schema, though it doesn't cover all possible nuances like format constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get top headlines for a country.' It specifies the verb ('Get') and resource ('top headlines'), and distinguishes it from siblings like get_category_feed or get_search_feed by focusing on headlines rather than categories or search results. However, it doesn't explicitly differentiate from get_geo_feed, which might be similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'for a country' but doesn't explain when to choose this over siblings like get_category_feed or get_topic_feed, nor does it specify prerequisites or exclusions. This lack of context leaves the agent without clear usage direction.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Get headlines' which implies a read-only operation, but doesn't mention any behavioral traits like rate limits, authentication requirements, pagination, or what happens if invalid parameters are provided. For a tool with 3 parameters and no annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 perfectly structured and concise. It starts with the core purpose, then provides a clear Args section with parameter details, and ends with Returns information. Every sentence earns its place by adding specific value, with no wasted words or redundant information.
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 has an output schema (though not shown here), the description doesn't need to explain return values in detail. It provides adequate parameter semantics and a clear purpose. However, as a read operation with no annotations and multiple sibling alternatives, it should include more behavioral context and usage guidance to be fully complete for an AI agent.
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 description adds substantial value beyond the input schema, which has 0% description coverage. It provides the complete enum list for the 'category' parameter (WORLD, NATION, BUSINESS, etc.), explains that 'language' and 'country' default to config values, and clarifies that only 'category' is required. This effectively compensates for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('headlines for a specific category'). It distinguishes itself from siblings like 'get_top_headlines' or 'get_geo_feed' by focusing on category-based filtering rather than geographic or search-based feeds. However, it doesn't explicitly contrast with 'get_topic_feed' or 'list_categories', leaving some sibling differentiation incomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_top_headlines' or 'get_search_feed'. It mentions the 'category' parameter but doesn't explain when category-based filtering is preferred over other filtering methods available in sibling tools. There are no explicit when/when-not statements or named alternatives.
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 carries the full burden. It states the tool lists categories and returns a dict with a list of names, which covers basic behavior. However, it lacks details on permissions, rate limits, error handling, or whether this is a read-only operation (implied but not stated). For a tool with zero annotation coverage, this is a significant gap in behavioral disclosure.
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?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, and the second sentence specifies the return value. There's no wasted text, but it could be slightly more structured (e.g., bullet points) for optimal clarity, so it's not a perfect 5.
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 low complexity (0 parameters, simple list operation), an output schema exists (implied by context signals), and no annotations, the description is fairly complete. It explains what the tool does and the return format. However, it could benefit from more behavioral context (e.g., read-only nature, any dependencies), so it's not a full 5.
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 tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as per the rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List available news categories for get_category_feed.' This specifies the verb ('List') and resource ('available news categories'), and mentions the sibling tool get_category_feed. However, it doesn't explicitly differentiate from other sibling tools like get_geo_feed or get_topic_feed, which might also involve categories, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by referencing get_category_feed, suggesting this tool should be used to retrieve categories for that specific sibling. However, it doesn't provide explicit guidance on when to use this tool versus alternatives (e.g., if other tools also list categories or if this is a prerequisite), and there are no exclusions or clear context beyond the implied link.
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 provided, the description carries full burden. It describes what the tool returns (feed title, description, article entries) which is helpful, but doesn't disclose important behavioral traits like rate limits, authentication needs, error conditions, or whether this is a read-only operation. The description adds some context but leaves significant 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 perfectly structured and front-loaded with the core purpose first, followed by topic ID explanation, parameter details, and return format. Every sentence adds value with zero wasted words, making it highly efficient for an AI agent to parse.
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 has an output schema (which covers return values) and the description explains parameters and purpose well, it's mostly complete. However, for a tool with no annotations, it should ideally mention that this is a read-only operation and any rate limits or authentication requirements to be fully 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?
With 0% schema description coverage and 3 parameters, the description compensates well by explaining topic_id as 'Google News topic hash identifier' and providing examples (cryptocurrency, AI). It also clarifies that language and country have defaults from config. However, it doesn't specify format requirements or valid values for language/country codes.
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 'Get' and resource 'news for a specific Google News topic ID', making the purpose explicit. It distinguishes from siblings like get_category_feed, get_geo_feed, and get_search_feed by specifying it's for topic-based feeds rather than category, geography, or search-based feeds.
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 clear context by explaining what topic IDs are (hashes for trending topics) and listing other feed types as siblings, but doesn't explicitly state when to use this tool versus alternatives like get_category_feed or get_search_feed. It implies usage for topic-based news but lacks explicit comparison guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: concurrent processing, fallback behavior for non-Google News URLs or failed decoding, and the specific return format. It doesn't mention rate limits, authentication needs, or error handling details, but covers the essential operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured with a clear purpose statement, behavioral details, and separate Args/Returns sections. Every sentence earns its place by providing essential information without redundancy, and it's front-loaded with the core functionality.
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 the tool's moderate complexity, no annotations, 0% schema coverage, but with an output schema, the description is complete enough. It explains what the tool does, how to use it, parameter details, and behavioral characteristics. The output schema handles return value documentation, so the description appropriately focuses on usage context.
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?
With 0% schema description coverage, the description fully compensates by providing detailed parameter semantics. It explains the 'urls' parameter as 'A list of Google News URLs to decode' with a concrete example format, adding crucial meaning beyond the bare 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 specific verb 'convert' and resource 'Google News URLs to their actual article URLs', with explicit scope 'multiple' and 'concurrently'. It distinguishes from sibling tools by focusing on URL decoding rather than news feed retrieval.
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 clear context about when to use this tool ('Convert multiple Google News URLs to their actual article URLs') and includes a fallback behavior ('If a URL is not a Google News URL or decoding fails, returns the original URL'). However, it doesn't explicitly mention when NOT to use it or compare it to specific alternatives among 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 full burden of behavioral disclosure. It effectively describes key behavioral traits: it performs a search operation (implying read-only, non-destructive behavior), supports advanced operators with examples, specifies a result limit ('up to 100 articles'), and outlines the return structure. It does not mention rate limits, authentication needs, or error handling, but covers core functionality well.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a bulleted list of advanced operators for quick reference, and then structured sections for Args and Returns. Every sentence earns its place by providing essential information without redundancy or fluff.
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 the tool's moderate complexity (3 parameters, advanced operators) and the presence of an output schema (which handles return value details), the description is complete enough. It covers purpose, usage with operators, parameter semantics, and behavioral traits like result limits, leaving the output schema to specify the exact return structure. No critical gaps are evident for effective tool selection and invocation.
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 description coverage is 0%, so the description must compensate fully. It adds significant meaning beyond the bare schema: it explains that 'query' supports advanced operators with detailed examples, clarifies that 'language' and 'country' are optional with defaults from config, and provides context on valid values (e.g., time range options like '1h', '24h'). This goes well beyond the schema's basic type definitions.
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 specific action ('Search Google News and get RSS feed for results'), distinguishing it from sibling tools like get_top_headlines (which likely returns headlines without search) or get_category_feed (which filters by category rather than search query). It precisely identifies both the verb (search and get) and resource (Google News RSS feed).
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 implies usage context through the mention of 'advanced search operators' and the specific return format, suggesting this tool is for customized news searches. However, it does not explicitly state when to use this tool versus alternatives like get_top_headlines or get_category_feed, nor does it provide exclusion criteria or prerequisites for use.
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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