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EfrainTorres

ArmaVita Meta Ads MCP

list_ad_previews

Generate previews of Meta ads to review creative elements, formatting, and localization before publishing campaigns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_idYes
meta_access_tokenNo
ad_formatNo
localeNo
render_typeNo
widthNo
heightNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `list_ad_previews` function is defined as an MCP tool in `src/armavita_meta_ads_mcp/core/ad_tools.py`. It fetches ad previews from the Meta API and implements a fallback mechanism if the API requires an explicit `ad_format`.
    @mcp_server.tool()
    @meta_api_tool
    async def list_ad_previews(
        ad_id: str,
        meta_access_token: Optional[str] = None,
        ad_format: Optional[str] = None,
        locale: Optional[str] = None,
        render_type: Optional[str] = None,
        width: Optional[int] = None,
        height: Optional[int] = None,
    ) -> str:
        if not ad_id:
            return _json({"error": "No ad ID provided"})
    
        params: Dict[str, Any] = {}
        if ad_format:
            params["ad_format"] = ad_format
        if locale:
            params["locale"] = locale
        if render_type:
            params["render_type"] = render_type
        if width is not None:
            params["width"] = width
        if height is not None:
            params["height"] = height
    
        payload = await make_api_request(f"{ad_id}/previews", meta_access_token, params)
    
        if not ad_format and _preview_requires_ad_format(payload):
            attempted_formats: List[str] = []
            for fallback_format in _PREVIEW_FALLBACK_AD_FORMATS:
                attempted_formats.append(fallback_format)
                fallback_params = dict(params)
                fallback_params["ad_format"] = fallback_format
                fallback_payload = await make_api_request(f"{ad_id}/previews", meta_access_token, fallback_params)
                if not (isinstance(fallback_payload, dict) and fallback_payload.get("error")):
                    if isinstance(fallback_payload, dict):
                        fallback_payload.setdefault("request_context", {})
                        if isinstance(fallback_payload["request_context"], dict):
                            fallback_payload["request_context"]["ad_format"] = fallback_format
                            fallback_payload["request_context"]["auto_selected"] = True
                    return _json(fallback_payload)
    
            if isinstance(payload.get("error"), dict):
                payload["error"]["attempted_ad_formats"] = attempted_formats
    
        return _json(payload)
Behavior1/5

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Conciseness1/5

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Completeness1/5

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Parameters1/5

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

Tool has no description.

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

Purpose1/5

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Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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