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anilsharmay

Country Explorer MCP Server

by anilsharmay

web_search

Search the web to gather country information for creating detailed profiles with embedded images and credits.

Instructions

Search the web for information about the given query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:14-18 (handler)
    The web_search tool handler, registered via @mcp.tool(). It takes a query string, uses the global TavilyClient to perform a web search, and returns the search results. The function signature and docstring define the input schema.
    @mcp.tool()
    def web_search(query: str) -> str:
        """Search the web for information about the given query"""
        search_results = client.get_search_context(query=query)
        return search_results
  • Global TavilyClient instance initialized with API key from environment, used by the web_search tool for performing searches.
    client = TavilyClient(os.getenv("TAVILY_API_KEY"))
  • server.py:14-14 (registration)
    Registration of the web_search tool using the FastMCP decorator.
    @mcp.tool()
Behavior2/5

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

With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't mention rate limits, authentication needs, result format, or other traits like pagination or safety considerations.

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 a single, efficient sentence with no wasted words, making it appropriately sized and front-loaded for clarity.

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 moderate complexity (searching the web), no annotations, and an output schema that likely handles return values, the description is incomplete. It lacks context on usage, parameters, and behavioral aspects, but the output schema may mitigate some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate but adds minimal meaning. It mentions 'query' but doesn't explain what constitutes a valid query, examples, or constraints beyond the schema's basic type.

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 verb ('search') and resource ('the web'), making the purpose understandable. It doesn't differentiate from sibling tools like 'unsplash_search' which might also search but for specific content, so it's not fully distinguished.

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 like 'unsplash_search' or other search methods. The description implies general web searching but lacks 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.

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