API Direct

search_facebook_posts

Search Facebook posts by keyword across all of Facebook. Optionally scope results to a place with location_id (resolve one via the search_facebook_locations tool).

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)
`sort_by`	No	Sort order: most_recent or relevance (default: relevance)	relevance
`end_date`	No	Filter posts until this date
`start_date`	No	Filter posts from this date
`location_id`	No	Facebook location ID (from search_facebook_locations) to scope results to a place
`get_sentiment`	No	Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedSep 4, 2026

changedInput schema / properties / pages / description

Previous 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 observedAug 17, 2026

TDQS

A4.2/5.0

Behavior3/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It clearly discloses the all-of-Facebook scope and the optional location filter, but it omits pagination behavior, per-page billing, and the sentiment-analysis surcharge, leaving those important operational traits only in the schema.

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?

Two terse sentences with no extraneous words. The primary action is front-loaded, and the optional location guidance is appended without diluting the core message.

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?

The schema fully documents all seven parameters, and the description adds the essential global scope and location-resolution context. The missing output schema and absent annotations leave minor ambiguity about result format, but the tool is straightforward enough that this is not a significant gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds real value by instructing the agent to resolve location_id via search_facebook_locations, which is a meaningful cross-tool usage hint beyond what the schema says.

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 opens with a specific verb and resource, 'Search Facebook posts by keyword across all of Facebook,' making the tool's core purpose immediately clear. It also distinctly separates this from sibling tools like search_facebook_pages or facebook_page_posts by emphasizing the global scope.

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

Usage Guidelines4/5

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

It provides explicit guidance for the optional location scoping, including a direct pointer to search_facebook_locations to resolve the location_id. However, it stops short of explicitly explaining when not to use this tool or naming alternatives for page- or group-specific post retrieval.

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.

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