Korean News Hub
Server Details
Korean news aggregator - Naver, Google News, Daum trends in real-time
- Status
- Unhealthy
- 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 3.5/5 across 6 of 6 tools scored. Lowest: 2.7/5.
Tools are mostly distinct, but trending (korea scope) and korean_news (with '속보' category) have overlapping functionality, and daily_briefing combines outputs from other tools. Otherwise well-separated.
All tool names use snake_case, but patterns vary: some are verb_noun (read_article), others noun_noun (tech_news), or gerund (trending). Not fully consistent but still readable.
With 6 tools covering news retrieval, search, reading, trending, and a combined briefing, the count is well-scoped for the server's purpose.
Core read operations are covered (category, search, read, trending, tech, briefing). Minor gaps: no date filtering or source selection, but 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 provided, the description carries full burden. It states what the tool does but omits details like data freshness, rate limits, or caching. For a simple no-param tool, this is minimally adequate.
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 sentences with no extraneous words. Front-loaded with the verb and purpose.
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 tool with no parameters and an output schema, the description covers the main purpose and composition. Could mention frequency or that no input is required, but overall adequate.
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?
Tool has 0 parameters, so schema coverage is 100%. Per guidelines, 0 parameters warrant a baseline of 4. The description correctly implies no input needed.
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 specifies the tool generates a comprehensive daily news briefing, combining specific topics (Korean headlines, AI/tech, Claude/Anthropic). This differentiates it from sibling tools like korean_news and tech_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?
The description implies usage for a consolidated briefing but does not explicitly state when to use this tool over siblings or provide exclusions. Usage context is clear but lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
korean_newsAInspect
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 provided, so description carries full burden. It correctly implies a read operation ('Get') but doesn't disclose any behavioral details like authentication, rate limits, or data freshness.
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?
Extremely concise: one sentence for purpose, then parameter list. No redundant information, easy to scan.
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 retrieval tool with an output schema, the description covers the basics well. However, it could mention language context or that it fetches recent articles. Still, it's sufficient.
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% for descriptions, but the description adds essential constraints: category options (속보, 정치, etc.) and count max (20) not in schema. Default values are also clarified.
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 Korean news by category,' specifying the verb and resource. It distinguishes from siblings like 'tech_news' by focusing on Korean news, but doesn't explicitly contrast with other news tools.
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 like 'news_search' or 'trending'. Context for choosing categories or handling default values is implied but not explicitly stated.
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 are provided, so the description must cover behavioral traits. It only lists parameters and defaults, omitting side effects, read-only nature, error handling, or any limitations beyond max count.
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: a one-line purpose followed by bullet points for parameters. Every sentence adds value with 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 that an output schema exists (reducing need to describe return values), the description covers all parameters with examples and constraints. It is complete for a simple search tool, though it could mention language restrictions more explicitly.
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?
With 0% schema coverage, the description compensates well by providing examples ('Samsung AI'), default values, and max count for 'count', and language examples. It adds useful context beyond the 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 'Search news by keyword,' identifying the verb (search) and resource (news). It distinguishes from siblings like daily_briefing or trending, which are more specific, but does not explicitly contrast 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 versus alternatives like daily_briefing or tech_news. The description only explains parameters but does not indicate preferred contexts or exclusions.
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?
Annotations are absent, so description must fully convey behavior. It only states 'Read and extract article content' without mentioning read-only nature, error handling, or any side effects. Minimal behavioral insight.
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?
Description is short, but includes redundant docstring repetition. Could be slightly more concise. Adequate but not exemplary.
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?
Output schema exists but description does not mention return format. No discussion of errors, limits, or contrast with siblings. Adequately covers the basic function 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?
Only one parameter 'url' with zero schema description coverage. Description adds 'The article URL to read', which merely restates the parameter name. Adds little value beyond the 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?
Description clearly states verb 'Read' and resource 'article content from a URL'. However, it does not differentiate from sibling tools like news_search or daily_briefing, which might also involve reading content.
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 news_search or trending. No mentions of prerequisites or context where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tech_newsAInspect
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 provided, so description carries full burden. Disclosures include default and max count, topic options, and 'global' scope. Adequate for a simple fetch tool.
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-sentence description plus args list. Front-loaded with purpose, then parameter details. No wasted words.
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?
Covers purpose and parameters well for a simple tool. Output schema exists (not shown) so return format is not needed. Lacks source or rate limit info, but sufficient for basic use.
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, but description compensates fully: explains topic options (including Korean terms), count default (10) and max (20). Adds meaning beyond 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?
Description clearly states 'Get global AI/tech news by topic', with specific verb and resource. Differentiates from siblings like korean_news (language-specific) and news_search (search).
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?
Provides topic options and count limits, implying when to use (fetch by topic). However, lacks explicit guidance on when not to use or alternatives (e.g., for specific articles use read_article).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trendingBInspect
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 must carry the behavioral burden. It correctly conveys that this is a read operation, but does not disclose any additional behaviors like rate limits, authentication, or edge cases (e.g., unrecognized scope values).
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 very concise (two sentences plus an args list) and front-loaded with the main action. However, it could be slightly more structured or include a brief usage note.
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 tool with one parameter, the description covers the basic purpose and parameter semantics. An output schema exists, so return values need not be described. However, the description lacks usage context relative to sibling tools, making it only adequately complete.
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 input schema has 0% description coverage for the scope parameter. The description compensates by explaining the options: 'korea' for Korean headlines and 'tech' for global tech trends, adding meaning beyond the 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 states 'Get current trending/headline news', clearly indicating a verb+resource. However, it does not differentiate from sibling tools like korean_news or tech_news, which may have overlapping functionality.
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 trending over alternatives such as daily_briefing, news_search, or korean_news. The description only explains the parameter but not the usage context.
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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