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datasets_facebook_pages_search

Search public Facebook Pages by contact details, category, likes, and discovery source to find business emails, phones, websites, or WhatsApp numbers.

Instructions

Search the Facebook Pages dataset. Searches public Facebook Page contact records stored in a search index — website, email, phone, WhatsApp, category and like count, discovered through business-search enumeration, domain-scoped scans, and Wikidata seeding, then hydrated from each Page's public About tab. Sort enum: relevance, likes_desc, likes_asc, hydrated_at_desc, hydrated_at_asc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over title and address, max 256 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, likes_desc, likes_asc, hydrated_at_desc, hydrated_at_asc
page_idNoExact Facebook Page id filter, max 128 characters
categoryNoExact Page category filter (case-insensitive), max 128 characters
has_emailNoFilter by a public contact email
has_phoneNoFilter by at least one public phone number
max_likesNoMaximum Page like count
min_likesNoMinimum Page like count
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
identifierNoExact Page username/identifier filter (case-insensitive), max 128 characters
has_websiteNoFilter by a linked website
has_whatsappNoFilter by a public WhatsApp contact
hydrated_afterNoRecords last refreshed on or after this date (RFC3339 or YYYY-MM-DD)
hydrated_beforeNoRecords last refreshed on or before this date (RFC3339 or YYYY-MM-DD)
discovery_sourceNoExact filter for how the Page was discovered (e.g. business_search, warc_domain_scan, wikidata), max 128 characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "likes_desc",
+  "likes_asc",
+  "hydrated_at_desc",
+  "hydrated_at_asc"
+]
  2. Addedv1.16.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the transparency burden. It adds helpful provenance context (records discovered via business-search enumeration, domain scans, Wikidata seeding, hydrated from About tabs) and lists the sort enum. However, it does not explicitly state read-only behavior, pagination, or result response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loads the action ('Search the Facebook Pages dataset') in the first sentence. The second sentence packs provenance and sort detail into one long, readable clause, though the sort enum duplicates schema info.

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?

The description tells the agent what dataset is searched and what fields exist, which is useful for selection, but it omits any direction to the item/facets siblings and doesn't describe result structure (no output schema). For a 16-parameter search tool with no annotations, this is adequate but leaves the agent to infer navigation and usage from the schema.

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 covers 100% of parameters with descriptions, so baseline is 3. The description only repeats the sort enum and loosely lists filterable fields (e.g., website, email, phone) that already appear in the schema, adding no new semantics.

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 explicitly says 'Search the Facebook Pages dataset' and specifies it searches public Facebook Page contact records in a search index, listing fields like website, email, phone, WhatsApp, category, and like count. This clearly identifies the tool as a search over Facebook Pages contacts and distinguishes it from singular/facets siblings by naming the search-index behavior.

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 given about when to use this search versus siblings like datasets_facebook_pages_item or datasets_facebook_pages_facets. The description implies usage by describing the search and sort options, but it never states exclusions or alternative routing.

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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