News Aggregator MCP Server

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation4/5
Most tools have clearly distinct purposes, but 'search_global_news' and 'search_rss_feeds' both search news using different backends (GDELT vs. RSS), which could cause initial confusion. Additionally, 'get_news_timeline' and 'get_trending_topics' both offer trend analysis, with one being query-specific and the other general. However, descriptions help mitigate overlap.
Naming Consistency5/5
All tool names follow a consistent 'verb_noun' pattern in snake_case, such as 'fetch_feed', 'get_hackernews_top', 'search_global_news', and 'list_feed_catalog'. No mixed conventions or vague verbs are used.
Tool Count5/5
11 tools is well-scoped for a news aggregator. It covers fetching arbitrary feeds, searching globally, searching RSS feeds, retrieving news by category/country, analyzing trends, and listing available feeds—without being overwhelming or too sparse.
Completeness5/5
The tool set provides comprehensive coverage of common news aggregation needs: arbitrary feed fetching, global search via GDELT, RSS search, category/country filtering, trend analysis, and a feed catalog. No significant gaps are apparent for the stated purpose.
Average 3.4/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry the behavioral burden. It implies a read-only operation but lacks details on side effects, authentication, rate limits, or whether the output format is consistent. The mention of 'limit' with a max is a minor positive, but overall transparency is low.
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 concise with a clear one-line purpose followed by a structured Args section. It is front-loaded and every sentence adds value, though it could be slightly more structured with a separate description line.
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?
For a simple 2-parameter tool with no output schema, the description covers the basics. However, it omits information about return values, error handling, or any rate limits, leaving gaps for an agent to fully understand the tool's behavior.
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 schema coverage at 0%, the description compensates by listing allowed values for story_type (top, new, best, ask, show, jobs) and documenting default and max for limit. This adds meaningful context that the schema does not provide.
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 it retrieves top stories from Hacker News using a specific verb ('abrufen') and resource. It distinguishes from sibling tools like get_hackernews_story (single story) and get_hackernews_trending (trending) through its focus on a list with filtering by story_type.
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?
No guidance is provided on when to use this tool versus alternatives such as fetch_feed or get_news_by_category. There are no hints about prerequisites or when not to use it.
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 must disclose behavioral traits but only states the basic function. It does not mention rate limits, data freshness, authentication needs, or whether the tool is read-only (though it likely is). This is a significant gap for safe invocation.
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 extremely concise: two sentences front-loading the purpose and specifying parameters with examples. No words are wasted.
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?
For a simple search tool with no output schema, the description covers input parameters adequately but omits output format and behavior (e.g., whether it returns full story objects or just titles). Given the sibling tools, this missing info could confuse the agent.
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 0%, so the description partially compensates by explaining that keywords are comma-separated and limit defaults to 5 with 'Maximale Treffer'. However, it does not clarify whether 'limit' applies per keyword or total, nor what constitutes a 'hit'.
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 it searches HackerNews top stories by keywords ('Sucht HackerNews Top-Stories nach Keywords.'). However, it does not distinguish this from related sibling tools like get_hackernews_top or search_global_news, missing an opportunity to clarify its specific scope.
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?
No guidance is provided on when to use this tool over its siblings. The description does not mention conditions or exclusions, leaving the agent to infer usage context from the name alone.
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 convey behavioral traits. It mentions the data source (GDELT) but omits details on rate limits, data freshness, or whether the operation is read-only. The parameter descriptions are present but incomplete on side effects.
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 concise with a one-line purpose and a structured Args section. No unnecessary content; each sentence serves a purpose.
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?
For a simple tool with two parameters and no output schema, the description covers the basics. However, it omits details about the return format or any pagination, which could be expected for a trending topics tool.
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 fills the gap by listing allowed values for timespan (1h, 4h, 1d, 3d, 7d) and tone_filter (positive, negative, neutral, empty). This adds significant meaning beyond the schema's defaults.
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 retrieves current trending topics worldwide via GDELT. The verb 'Ermittelt' (determines) and resource 'aktuelle Trending-Themen weltweit' are specific. While it distinguishes from sibling tools like get_hackernews_trending, it does not explicitly differentiate, leaving some ambiguity.
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_hackernews_top or search_global_news. It only describes functionality without context for selection.
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 transparency. It does not disclose any safety implications (e.g., read-only nature), side effects, or constraints. The description only describes the basic function without addressing behavioral traits.
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 concise and well-structured, with a clear one-sentence purpose followed by parameter descriptions. It avoids unnecessary verbosity, though the German language does not affect scoring. Every sentence adds value.
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 lack of output schema and annotations, the description covers the input parameters adequately but does not describe the output format, pagination, or any error conditions. For a search tool with three parameters, this is minimally complete but leaves some gaps.
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 significant meaning beyond the schema by including an 'Args' block with explanations for each parameter: examples for query, explanation of categories (comma-separated or 'all'), and default value for max_results. Since schema description coverage is 0%, the description effectively compensates.
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 'Durchsucht Nachrichten in allen Kategorien nach einem Suchbegriff', which specifies the action (searching), resource (news in all categories), and required input (search term). It distinguishes itself from siblings by explicitly mentioning 'all categories', but could be more specific in differentiating from similar tools like search_global_news.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or scenarios where other tools might be preferred. The description only explains what the tool does, not when to invoke it.
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 only mentions 'aggregates news from predefined sources', but does not disclose whether the operation is safe, idempotent, or involves external API calls. No information on rate limits, authentication, or side effects is given.
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 extremely concise, consisting of a single sentence and a clear bullet-like listing of parameters. Every word serves a purpose, and there is no redundant information. The structure prioritizes key information upfront.
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 simplicity (2 parameters, no output schema, no annotations), the description covers the essential purpose and parameter details. However, it lacks completeness regarding the output format, behavior when no results are found, and the nature of the 'predefined sources'. For a tool with siblings, it could benefit from brief disambiguation.
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 has 0% description coverage, but the description adds significant meaning: it enumerates possible values for 'category' (tech, ai, general, business, crypto, science) and explains that 'max_per_feed' controls articles per feed with a default of 3. This goes beyond the schema's bare type declarations.
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 that the tool aggregates news from predefined sources for a given category, using the specific verb 'aggregiert' and resource 'Nachrichten aus vordefinierten Quellen einer Kategorie'. While it does not explicitly distinguish itself from siblings like get_news_by_country, the category-focused purpose is evident from the name and description.
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 lacks explicit context for when to prefer this over sibling tools like get_news_by_country or fetch_feed. The usage is only implied by the tool's name and description.
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 disclose behavioral traits. It only states the tool returns structured articles and parameter defaults, but lacks information about authentication, rate limits, error handling, or side effects like network delays.
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 very concise: two sentences plus an args list. No extraneous words, information is front-loaded with the main purpose.
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 no output schema and no annotations, the description covers the tool's function and parameters but lacks details on output format, error scenarios, and usage context. It is adequate but not fully comprehensive.
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 coverage, the description adds meaningful explanations for both parameters: feed_url is described as a URL with an example, and max_articles specifies default and max values, adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (fetch) and resource (RSS/Atom feed) and outcome (structured articles). It distinguishes from sibling tools like get_hackernews_story or get_news_by_category which target specific sources or categories.
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 siblings. It doesn't mention conditions for choosing fetch_feed over list_feed_catalog or search_rss_feeds.
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 provided. The description only declares the action without disclosing behavioral traits such as idempotency, rate limits, or whether the catalog is static or dynamic.
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?
Single concise sentence with no waste. However, could be slightly more structured by including a brief note on the catalog's purpose.
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 zero parameters and no output schema, the description covers the essential purpose. It could mention that the catalog feeds are usable with other tools, but not mandatory.
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?
No parameters exist, so baseline score of 4 applies. The description adds no parameter info, which is acceptable given zero parameters and 100% schema coverage.
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 returns a complete catalog of predefined news feeds, using specific verb 'returns' and resource 'catalog'. It distinguishes from sibling tools that fetch individual feeds or search.
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?
No guidance on when to use this tool versus alternatives like fetch_feed or search tools. The description implies it's for listing available feeds, but no explicit context or exclusions.
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. The description does not disclose read-only nature, side effects, authentication needs, or response format. This is a significant gap for a tool that likely fetches external data.
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 concise with one sentence and one parameter explanation. It is front-loaded and efficient, though the parameter description could be integrated more elegantly.
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 simplicity (single parameter, no output schema, no annotations), the description is minimally adequate. However, it lacks details on what 'details' entail and any limitations, leaving completeness to be desired.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining the parameter as 'Numerische ID der HN-Story' with an example, adding meaning beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves details for a specific HackerNews story, specifying the exact resource. It differentiates from siblings like get_hackernews_top (lists top stories) by focusing on a single story by ID.
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 when a specific story ID is known, but lacks explicit guidance on when to prefer alternatives or any exclusions. It is implicit from the tool's purpose.
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 bears full responsibility for behavioral disclosure. It only states that the tool analyzes volume over time, but does not disclose whether it is read-only, any authentication requirements, rate limits, or what happens if the query is invalid. The mutation status is implied as safe but not confirmed.
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 extremely concise: two sentences front-loaded with purpose, followed by a clear argument list. Every piece of information is relevant and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (trend analysis over time) and the lack of an output schema, the description is incomplete. It does not explain what the output looks like (e.g., an array of time points with counts, intervals), nor does it mention pagination or data limits. For a tool that returns a timeline, this is a significant gap.
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 value beyond the input schema by explaining 'query' as the topic or search term and 'timespan' as the time period with allowed values (15min, 1h, etc.) and a default. This compensates for the schema's lack of descriptions (0% coverage). However, it does not clarify the exact format for the timespan values (e.g., '1d' vs '1 day').
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 analyzes news volume over time for a topic, which is a specific verb and resource. This distinguishes it from siblings like search_global_news (which searches for news articles) and get_trending_topics (which gets trending topics rather than volume trends).
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 for trend analysis via the phrase 'Trend-Analyse', but it does not explicitly state when to use this tool versus alternatives like search_global_news or get_news_by_category. No exclusions or prerequisites are mentioned.
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, and the description lacks behavioral details such as rate limits, authentication, data freshness, or return behavior (e.g., errors, empty results). Only parameter descriptions are given.
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 concise, using a brief introductory sentence followed by clear bullet points for each parameter. 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?
For a simple retrieval tool with no output schema, the description adequately covers all parameters and provides examples. It could mention the return format, but overall it is sufficient for effective use.
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?
Despite 0% schema coverage, the description adds significant meaning: it specifies country_code format (2-letter codes with examples), optional query, and default for max_records. This compensates well for the sparse 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 it retrieves news from a specific country using a verb ('abrufen') and resource ('Nachrichten aus einem bestimmten Land'). It effectively differentiates from siblings like search_global_news and get_news_by_category by focusing on the country dimension.
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 for country-specific news but does not explicitly state when to use this tool vs alternatives (e.g., search_global_news for broader queries, get_news_by_category for category). No exclusions or context provided.
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 explains the source (GDELT) and scope, but lacks details on returned data format, pagination, rate limits, or data freshness. It is adequate but not comprehensive.
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 concise, with two sentences stating purpose followed by a clear bulleted list for parameters. No unnecessary information; every sentence adds value.
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?
While the input parameters are well-covered, the description omits any details about the output format. Since there is no output schema, explaining what the search returns (e.g., article title, source, date) would improve completeness for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description provides detailed semantics for all four parameters in the Args section, including examples (e.g., 'AI regulation'), mode options (artlist, artgallery), default/max for max_records, and language examples. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches global news via GDELT, covering 65+ languages and 100+ countries. This distinguishes it from sibling tools like fetch_feed or get_news_by_country, which are more specific. The verb 'search' is specific to the resource.
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 for broad global news search through its coverage explanation, but it does not explicitly state when to use or not use this tool versus siblings. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![news-aggregator-mcp-server MCP server](https://glama.ai/mcp/servers/AiAgentKarl/news-aggregator-mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/AiAgentKarl/news-aggregator-mcp-server)

Score Badge

Copy to your README.md:

[![news-aggregator-mcp-server MCP server](https://glama.ai/mcp/servers/AiAgentKarl/news-aggregator-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/AiAgentKarl/news-aggregator-mcp-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AiAgentKarl/news-aggregator-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server