Get videos from a Facebook page. Requires the delegate_page_id from the page details endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | Number of pages to fetch (1-15, default 1). Billed per page. | |
| 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. | |
| delegate_page_id | Yes | Delegate page ID (from page details endpoint) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of exposing behavior. It only mentions the data dependency and not pagination, per-page billing, sentiment surcharge, response format, or any rate/auth constraints. Minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with purpose ready and the key prerequisite stated up front. No filler, but the first sentence largely repeats the tool name and valuable usage guidance is absent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite decent parameter descriptions, there are no annotations or output schema, and the description does not explain billing, paging behavior, sentiment add-on implications, or when to use this vs video-search/reel siblings. An agent can make a basic call but cannot fully configure or route optimally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is effectively 100%: pages, get_sentiment, and delegate_page_id all have meaningful descriptions. The tool description adds little beyond restating the delegate_page_id source, so the schema does the heavy lifting and baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource: 'Get videos from a Facebook page.' It also identifies the required input, delegate_page_id, but it does not explicitly differentiate videos from the related sibling tools like facebook_page_reels or search_facebook_videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a prerequisite—that delegate_page_id comes from the page details endpoint—but gives no guidance on when to choose this tool over search_facebook_videos, facebook_page_posts, or facebook_page_reels. No exclusions or alternative routing are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.