Korean News Hub
Server Details
Korean news aggregator - Naver, Google News, Daum trends in real-time
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- SongT-50/korean-news-mcp
- GitHub Stars
- 0
- Server Listing
- korean-news-mcp
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Tool Definition Quality
Average 3.4/5 across 6 of 6 tools scored. Lowest: 2.8/5.
Each tool has a distinct purpose: daily briefing, category-based news, keyword search, article reading, tech news, and trending. There is slight overlap between korean_news with IT category and tech_news, and between trending and korean_news, but descriptions clarify the differences.
Tool names follow no single pattern: daily_briefing (adj_noun), korean_news (adj_noun), news_search (noun_noun), read_article (verb_noun), tech_news (noun_noun), trending (adjective). The mix of conventions is functional but not perfectly consistent.
Six tools cover the core functionalities of a news hub without bloat. Each tool adds clear value, and the count aligns well with the server's scope.
The tool set covers essential news operations: category browsing, keyword search, article reading, trending, tech news, and a daily briefing. Missing features like date filtering or user preferences are minor gaps that agents can work around.
Available Tools
6 toolsdaily_briefingAInspect
Generate a comprehensive daily news briefing. Combines Korean headlines + AI/tech news + Claude/Anthropic news.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states that it generates a briefing. It does not disclose behavioral traits such as read-only nature, rate limits, or potential side effects, though the read-only nature is obvious. The output schema exists but description adds no extra context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two succinct sentences with no wasted words. It is front-loaded with the main purpose and then adds details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, an output schema exists to describe return values, and siblings are present, the description adequately covers what the tool does and when to use it. No further information is needed.
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?
There are no parameters, and schema coverage is 100% (trivial). Baseline for 0 parameters is 4. The description adds value by explaining the content categories, which compensates for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a comprehensive daily news briefing, and specifies the content mix (Korean headlines, AI/tech news, Claude/Anthropic news). This distinguishes it from sibling tools like korean_news, tech_news, and news_search, which cover individual categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool should be used for a combined daily briefing, while siblings like korean_news and tech_news are for separate categories. However, it does not explicitly state when not to use it or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
korean_newsBInspect
Get Korean news by category.
Args:
category: News category. Options: 속보, 정치, 경제, 사회, IT, 세계, 연예, 스포츠
count: Number of articles (default 10, max 20)
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| category | No | 속보 |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
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 discloses default count and max limit, but does not mention behavior for invalid categories, rate limits, or response structure. Adequate but minimal.
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?
Very concise: two lines with an Args block. Every word is useful. No fluff.
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?
The tool has an output schema (not shown), so return values are covered. However, the description lacks context on when to use it among sibling tools and doesn't mention any prerequisites or edge cases. Adequate for a simple 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 coverage is 0%, but the description adds significant meaning by listing all category options and specifying count defaults/max. This compensates well for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('Korean news'), and lists specific categories. It differentiates from sibling tools by focusing on Korean news categories, though it doesn't explicitly contrast with siblings.
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 guidance is provided on when to use this tool versus alternatives like news_search, tech_news, or daily_briefing. The description only states what it does 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.
news_searchBInspect
Search news by keyword.
Args:
query: Search keyword (e.g. "Samsung AI", "Claude Code", "MCP server")
language: "ko" (Korean) or "en" (English)
count: Number of articles (default 10, max 20)
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| query | Yes | ||
| language | No | ko |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Does not disclose return format, performance, rate limits, or any side effects. Merely describes search action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise and well-structured using 'Args' section. No fluff, but could be slightly more compact. Front-loaded with clear verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given presence of output schema (not shown), description is acceptable but could mention result format or context for searching news specifically. Sibling tools suggest niche variations, but description does not address them.
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 has 0% description coverage. Description adds examples for query, specifies language options ('ko'/'en'), and defines count range (default 10, max 20), significantly enhancing parameter understanding.
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?
Description clearly states 'Search news by keyword' - specific verb+resource. However, does not differentiate from sibling tools like korean_news or tech_news, which also search news.
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 guidance on when to use this tool versus alternatives. Lacks when-not or context for selecting this over daily_briefing, korean_news, etc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_articleCInspect
Read and extract article content from a URL.
Args:
url: The article URL to read
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states the basic action but omits details like read-only nature, error handling, authentication needs, or limitations on article access.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct, with two sentences that front-load the key action. It is efficient and avoids unnecessary words, though it could include more useful details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema that likely explains return values, the description is partially complete. However, it lacks context on scope (e.g., full text or metadata) and constraints, which a well-rounded description would include.
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?
The parameter 'url' has no schema description (0% coverage), and the description only adds 'The article URL to read', which adds minimal meaning beyond the parameter name. It does not specify expected format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read and extract article content from a URL', specifying the action and resource. However, it does not explicitly differentiate from siblings like news_search or trending, though the intent is implied.
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 description provides no guidance on when to use this tool versus alternatives. It lacks explicit context for usage and does not mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tech_newsBInspect
Get global AI/tech news by topic.
Args:
topic: Tech topic. Options: AI, Claude, OpenAI, MCP, OpenClaw, 스타트업, 개발, 클라우드
count: Number of articles (default 10, max 20)
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| topic | No | AI |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It does not mention whether the tool is read-only, destructive, cached, or requires authentication. The return format is covered by the output schema but not referenced, leaving gaps in behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured. The purpose is front-loaded, followed by clear parameter documentation. Every sentence is necessary and informative with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 params, no nesting) and the presence of an output schema, the description is minimally adequate. However, it lacks usage guidelines and behavioral context, making it incomplete for a fully informed agent decision.
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?
The description fully compensates for 0% schema coverage by listing all topic options and specifying count constraints (default 10, max 20). This adds significant meaning beyond the schema, which only provides defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get global AI/tech news by topic,' specifying a verb ('Get'), resource ('global AI/tech news'), and scope ('by topic'). It distinguishes from siblings like korean_news (language-specific) and news_search (search-based) but does not explicitly compare to them.
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 guidance on when to use this tool vs alternatives such as daily_briefing or news_search. The description only provides topic options but no context on selecting this over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trendingAInspect
Get current trending/headline news.
Args:
scope: "korea" (Korean headlines) or "tech" (global tech trends)
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | korea |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It explains the basic behavior (retrieving trending news) and the scope options, but lacks details on data source, update frequency, or read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, front-loading the purpose. Every word is necessary and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description covers the essential points: purpose and parameter options. However, it lacks differentiation from similar sibling tools, which is a minor gap.
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?
The schema has 0% description coverage, but the description adds significant value by explicitly listing the two possible values for 'scope' ('korea' for Korean headlines, 'tech' for global tech trends). This clarifies parameter meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get current trending/headline news', using a specific verb and resource. However, it does not differentiate from sibling tools like 'korean_news' or 'tech_news', which may cause ambiguity.
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 guidance on when to use this tool versus alternatives. The description only mentions the scope parameter values but does not provide when/why to choose this tool over siblings like 'daily_briefing' or 'news_search'.
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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