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korean-data-mcp

search_daangn

Find items for sale on Daangn Market (당근마켓) using keyword and optional region filter. Returns listings with customizable max count up to 100.

Instructions

Search Daangn Market (당근마켓) listings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesSearch keyword in Korean or English
regionNoOptional region filter (e.g. '서울', '강남구')
max_itemsNoMaximum number of listings to return (default 30, max 100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Handler function for the 'search_daangn' MCP tool. Accepts keyword, optional region, and max_items; caps max_items at 100; delegates to the Apify actor 'oxygenated_quagmire/daangn-market-scraper'.
    @mcp.tool()
    async def search_daangn(
        keyword: str,
        region: str = "",
        max_items: int = 30,
    ) -> list[dict]:
        """
        Search Daangn Market (당근마켓) listings.
    
        Args:
            keyword: Search keyword in Korean or English
            region: Optional region filter (e.g. '서울', '강남구')
            max_items: Maximum number of listings to return (default 30, max 100)
    
        Returns:
            List of listing objects with title, price, location, image, url fields.
        """
        max_items = min(max_items, 100)
        input_data: dict[str, Any] = {"keyword": keyword, "maxItems": max_items}
        if region:
            input_data["region"] = region
        return await _run_actor(
            f"{APIFY_ACCOUNT}/daangn-market-scraper",
            input_data,
        )
  • Registration of 'search_daangn' as an MCP tool via the @mcp.tool() decorator from FastMCP.
    @mcp.tool()
  • Input schema: keyword (str, required), region (str, optional, default ''), max_items (int, optional, default 30, max 100). Output: list[dict].
    async def search_daangn(
        keyword: str,
        region: str = "",
        max_items: int = 30,
    ) -> list[dict]:
  • Helper function that runs an Apify actor and returns dataset items. Called by search_daangn to invoke 'daangn-market-scraper'.
    async def _run_actor(actor_id: str, input_data: dict, timeout_secs: int = 60) -> list[dict]:
        """Run an Apify actor synchronously and return dataset items."""
        token = _get_token()
        url = f"{APIFY_BASE}/acts/{actor_id}/run-sync-get-dataset-items"
        params = {"token": token}
    
        async with httpx.AsyncClient(timeout=timeout_secs + 10) as client:
            resp = await client.post(url, json=input_data, params=params)
            resp.raise_for_status()
            return resp.json()
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states 'Search listings' with no mention of pagination, rate limits, or any side effects.

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?

A single sentence that is direct and contains no superfluous information. Efficient communication.

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?

Despite having an output schema, the description fails to provide context about the tool's scope, behavior, or what constitutes a listing. It is too minimal for a complex search tool.

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?

The schema description covers 100% of parameters, so the description adds no extra value. According to guidelines, baseline 3 is appropriate when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('Search') and the specific resource ('Daangn Market listings'), distinguishing it from sibling tools like search_bunjang which targets a different marketplace.

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 such as search_bunjang or search_naver_places. The description lacks context for selection.

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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