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All About Ads MCP

start_facebook_ads_scrape

Initiate a background Facebook Ads Library scrape to run multiple search campaigns in parallel. Returns a run_id to monitor progress and collect results.

Instructions

Start a Facebook Ads Library scrape in the background and return a run_id immediately.

Use this instead of search_facebook_ads when running multiple scrapers in parallel. Call check_run_status to monitor progress, then collect_scrape_results once SUCCEEDED.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_typeNoAd type filter: ALL, POLITICAL_AND_ISSUE_ADS, HOUSING_ADS, EMPLOYMENT_ADS, or CREDIT_ADS.ALL
countryNoISO country code to filter by, e.g. 'US', 'IN', or 'ALL'. None for no filter.
sort_byNoSort order: SORT_BY_TOTAL_IMPRESSIONS or SORT_BY_RELEVANCY_MONTHLY_GROUPED.SORT_BY_TOTAL_IMPRESSIONS
end_dateNoLatest ad delivery date in YYYY-MM-DD format. None for no upper bound.
media_typeNoMedia type filter: ALL, IMAGE, MEME, IMAGE_AND_MEME, VIDEO, or NONE.ALL
start_dateNoEarliest ad delivery date in YYYY-MM-DD format. None for no lower bound.
active_statusNoAd status filter: ALL, ACTIVE, or INACTIVE.ALL
search_queriesYesKeywords or brand names to search for, e.g. ['nike', 'adidas'].
content_languagesNoLanguage codes to filter ad content by, e.g. ['en', 'fr'].
publisher_platformsNoPlatforms to filter by, e.g. ['facebook', 'instagram'].
max_results_per_queryNoMaximum ads to return per query. Minimum 10 (actor limit).
enrich_with_ad_detailsNoFetch extra per-ad details. Slower and uses more Apify credits.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintYes
run_idYes
statusYes
Behavior4/5

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

Annotations indicate this is not read-only and interacts with external systems. The description adds behavioral context: it runs in the background and returns immediately. It does not contradict annotations.

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?

Three sentences, front-loaded with purpose, then usage guidance, then workflow. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 12 parameters and an output schema, the description covers the essential aspects: async nature, parallel usage, and follow-up steps. Could mention the underlying platform (Apify) but not necessary.

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 coverage is 100% with well-described parameters. The description does not add parameter-specific meaning beyond the schema, which is acceptable given high coverage.

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 states the verb 'start', the resource 'Facebook Ads Library scrape', and the output 'run_id'. It distinguishes from sibling tool 'search_facebook_ads' by explicitly mentioning parallel scraping.

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly recommends using this tool instead of 'search_facebook_ads' when running multiple scrapers in parallel, and provides a clear workflow: call 'check_run_status', then 'collect_scrape_results' once SUCCEEDED.

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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