search_facebook_pages
Search Facebook pages by keyword.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | Number of pages to fetch (1-15, default 1). Billed per page. | |
| query | Yes | Search keyword (max 500 characters) |
API Direct
by io.apidirect
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Changed1 schema field changed
- changed
Input schema / properties / pages / descriptionPrevious value: -"Number of pages to fetch (1-10, default 1). Billed per page."New value: +"Number of pages to fetch (1-15, default 1). Billed per page."
- First observed
TDQS
C2.9/5.0
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 of behavioral disclosure. It only says 'Search Facebook pages by keyword' and does not mention result shape, pagination behavior, rate limits, or scope limitations like public pages only. This is a minimal statement rather than a transparent behavioral disclosure.
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 a single sentence with no filler and the core action is front-loaded. It is structurally efficient, though slightly under-specified for the broader selection context; still, this is a genuine conciseness strength rather than a verbosity problem.
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?
With no output schema and no annotations, the description is the only behavioral context available. It omits what returned page results look like, how results are ordered, and when this search should be preferred over neighboring Facebook search tools. This is too thin for confident tool selection among many siblings.
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 parameters are already documented and the baseline is 3. The description's 'by keyword' vaguely maps to the query parameter but adds no new information about pages, pagination, or billing. It neither improves nor harms parameter understanding.
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 identifies the action: search Facebook pages by keyword. It is unambiguous about the resource type, but it does not differentiate this tool from siblings like search_facebook_posts, search_facebook_videos, or search_facebook_events, so an agent may need extra inference to pick the right one.
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?
There is no guidance about when to use this tool versus alternatives such as search_facebook_posts, facebook_page_details, or search_facebook_locations. The description only restates the operation and provides no context, exclusions, or routing hints.
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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TDQS
B3.1/5.0
Disambiguation4/5
Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.
Naming Consistency4/5
The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.
Tool Count2/5
74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.
Completeness4/5
The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.