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mcp-ai-agent-server

mcp-ai-agent-server

by elcaiseri
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

fetch_news

Retrieve news articles for a search query. Control the number of results and language.

Instructions

Fetch news articles on a topic.

Args: topic: Search query/topic limit: Number of articles to return language: Language code (default: en)

Returns: Dictionary with news articles

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "<topic>"
    },
    "name": "fetch_news"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
topicYes
languageNoen

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and description fails to disclose behavioral traits like performance, rate limits, or side effects. It only describes the return type as a dictionary.

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?

Description is concise with a clear front-loaded purpose. Args listed in a structured but brief format. No unnecessary sentences.

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?

No output schema or annotations exist, and description does not specify news source, format, or error behavior. Inadequate for a tool with 3 parameters.

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% per context, but the description lists all three parameters with defaults that duplicate schema info. No additional meaning beyond schema fields.

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 'Fetch news articles on a topic' with a specific verb and resource. It distinguishes from sibling 'fetch_webpage' by focusing on news, though not explicit.

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_webpage' or when not to use it. Implied usage only.

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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