AgentNews
Server Details
Real-time news intelligence — Hacker News top/trending stories and The Guardian article search. Topic-based trending combining HN + Guardian across AI, crypto, science, tech, politics.
- Status
- Healthy
- Uptime
- 26.8% over 73 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2024-11-05
- URL
TDQS
Scored across 3 tools
get_top_news retrieves Hacker News top stories, while get_trending combines Hacker News and The Guardian for a given topic. These could be confused when a user wants top stories across sources, but the descriptions make the distinction clear. search_guardian is clearly separate in source and action.
All names use snake_case and follow a verb-first pattern: get_top_news, get_trending, search_guardian. The only minor deviation is that get_trending lacks an explicit noun, and one tool uses search_ instead of get_. Overall predictable.
Three tools is a small but reasonable scope for a focused news aggregation server covering top Hacker News, combined trending, and Guardian search. It feels slightly thin but each tool has a clear role.
The surface covers top Hacker News, combined trending by topic, and Guardian search, but lacks Hacker News search and Guardian top-stories retrieval. These are notable gaps for symmetric source coverage, though core news retrieval workflows are partially supported.
Available Tools
3 toolsget_top_newsBInspect
Get top stories from Hacker News. Returns title, URL, score, author, and comment count.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Story type: top, new, best, ask, show (default: top) | top |
| limit | No | Number of stories (max 30, default 20) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it usefully discloses the returned fields (title, URL, score, author, comment count) — valuable since there is no output schema. However, it omits rate limits, pagination, or caching behavior, and 'top stories' understates the type parameter's new/best/ask/show modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, zero padding, with the action front-loaded and the return payload immediately after. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with full schema coverage and no annotations, the description covers purpose and return shape, which compensates for the absent output schema. It could be complete with a note on the type parameter's scope (top/new/best/ask/show) so 'top stories' is not misleading.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (type and limit, including defaults and the max of 30) are already fully documented in the schema. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific verb + resource: 'Get top stories from Hacker News,' and it names the upstream source, which separates it from siblings like get_trending and search_guardian that target other feeds. It stops short of explicitly contrasting itself with those siblings, but the source naming does the routing work.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use, when-not-to-use, or alternative guidance is given. There is no hint about when to prefer this over get_trending or search_guardian, leaving the agent to infer everything from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trendingBInspect
Get trending news combining Hacker News and The Guardian for a given topic.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of items (max 30, default 10) | |
| topic | No | Topic: ai, crypto, science, politics, tech (default: tech) | tech |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It reveals the aggregation of two sources, which is genuinely useful behavioral context, but says nothing about whether results are merged or ranked, rate limits, network calls, or that the limit is capped at 30 (that detail lives only in the schema).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single 14-word sentence leading with the verb and resource, with the differentiating detail (the two sources) front-loaded. Nothing is padded and nothing needs to be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, all-optional read tool with no output schema, the description is minimally adequate but leaves the main ambiguity unresolved: how get_trending differs from get_top_news, and whether the limit applies per source or to the combined result. There is no output schema to offload those questions to.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (limit, topic, including their defaults and allowed topic values) are already fully documented in the schema. The description's 'for a given topic' merely restates the topic parameter without adding format or semantics, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (get) and resource (trending news) and even names the two upstream sources, Hacker News and The Guardian. It does not, however, distinguish itself from the sibling get_top_news, so an agent cannot tell from the description alone which of the two it should call.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this rather than get_top_news or search_guardian, no exclusions, and no prerequisites. The mention of 'a given topic' implies the topic parameter is the selector, but that is schema-level information, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_guardianCInspect
Search The Guardian for news articles. Supports filtering by section and date.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Search query (default: artificial intelligence) | artificial intelligence |
| limit | No | Number of articles (max 25, default 10) | |
| section | No | Section filter: technology, science, business, world, politics | |
| date_from | No | Filter articles from this date (YYYY-MM-DD) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It implies a read-only search but discloses nothing about result ordering, pagination, rate limits, or whether the search covers full text versus headlines. Only the query surface is mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with no filler; the core purpose leads. It is efficient, though quite thin for a tool with four parameters and no behavioral disclosure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple all-optional search tool with 100% schema coverage and no output schema, the essentials are present. However, the absence of routing guidance against the two sibling tools and any behavioral context leaves a visible gap for an unannotated tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters including defaults, the 25-item cap, and the date format. The description adds no syntax or semantic detail beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a clear verb+resource: 'Search The Guardian for news articles', which an agent can immediately understand. It does not, however, distinguish this query-based tool from the sibling browsing tools get_top_news and get_trending, so the selection decision rests on the name alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The sentence 'Supports filtering by section and date' describes capability, not when to use this tool. There is no guidance on when search_guardian is preferable to get_top_news or get_trending, and no stated preconditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
- First observed
get_top_news - First observed
get_trending - First observed
search_guardian
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceRemote MCP server that lets AI assistants read tracked competitive intelligence — competitor news, reviews, website changes, social posts and ads — and act on it by managing projects, competitors, battle cards, reports and canvases. Every answer carries a source and a date, and write actions only publish when explicitly shared.MIT
- AlicenseCqualityBmaintenanceCompetitor Monitor AI - MCP server providing AI-powered tools and automation by MEOK AI Labs115 npm55 PyPIMIT
- AlicenseAqualityCmaintenanceEnables brand visibility monitoring across major AI platforms like ChatGPT, Claude, Gemini, and Perplexity. It allows users to track visibility scores, analyze competitor data, and receive actionable insights to improve AI-generated brand recommendations.1618 npm1MIT

industrylens-mcpofficial
AlicenseNot gradedqualityBmaintenanceBrowse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.