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JanNafta

PropellerAds MCP Server

by JanNafta

list_campaigns

Retrieve and filter advertising campaigns by status, ad format, or name to monitor performance and manage campaign data.

Instructions

List all campaigns with optional filters. Returns campaign ID, name, status, ad format, and basic metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by status: active, paused, pending, rejected
ad_formatNoFilter by ad format: push, onclick, interstitial, in-page-push
nameNoFilter by campaign name (partial match)

Implementation Reference

  • The implementation of the list_campaigns method in the client class that performs the API call.
    def list_campaigns(
        self,
        status: str | None = None,
        ad_format: str | None = None,
        name: str | None = None,
    ) -> list[dict[str, Any]]:
        """List all campaigns with optional filters."""
        params = {}
        if status:
            params["status"] = status
        if ad_format:
            params["ad_format"] = ad_format
        if name:
            params["name"] = name
    
        result = self._request("GET", "/adv/campaigns", params=params or None)
        return result.get("data", result) if isinstance(result, dict) else result
  • The MCP tool registration for list_campaigns.
    Tool(
        name="list_campaigns",
        description="List all campaigns with optional filters. Returns campaign ID, name, status, ad format, and basic metrics.",
        inputSchema={
            "type": "object",
            "properties": {
                "status": {
                    "type": "string",
                    "description": "Filter by status: active, paused, pending, rejected",
                    "enum": ["active", "paused", "pending", "rejected"],
                },
                "ad_format": {
                    "type": "string",
                    "description": "Filter by ad format: push, onclick, interstitial, in-page-push",
                },
                "name": {
                    "type": "string",
                    "description": "Filter by campaign name (partial match)",
                },
            },
        },
    ),
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions optional filters and return fields, but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, any rate limits, pagination handling, or default sorting. For a listing tool with no annotations, this leaves significant gaps in understanding its behavior.

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 highly concise and front-loaded, consisting of two clear sentences. The first states the action and optional filters, and the second specifies return fields. There is no wasted verbiage, making it easy to parse quickly.

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 (listing with filters), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and return fields but lacks behavioral context and usage guidelines. For a tool with no output schema, it helpfully lists return fields, but overall completeness is limited by missing operational details.

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 100%, so the input schema fully documents the parameters (status, ad_format, name) with descriptions and enums. The description adds minimal value beyond this, only noting that filters are 'optional' and implying they refine the listing. No additional syntax, format, or usage details are provided beyond what the schema offers.

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 tool's purpose: 'List all campaigns with optional filters.' It specifies the verb ('List') and resource ('campaigns'), and mentions the return fields. However, it doesn't explicitly differentiate from sibling tools like 'get_campaign_details' or 'get_campaign_performance', which might offer more detailed or performance-focused campaign data.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_campaign_details' (likely for specific campaigns) and 'get_campaign_performance' (likely for metrics), there's no indication of when this listing tool is preferred, such as for overviews or bulk retrieval. Usage is implied but not stated.

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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