Get posts from a public Facebook group.
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | Number of pages to fetch (1-15, default 1). Billed per page. | |
| sort_by | No | Sort order: most_recent or relevance (default: most_recent) | most_recent |
| group_id | Yes | Facebook group ID (numeric) | |
| 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. |
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, the description carries the full behavioral disclosure burden, but it only restates the basic action. It does not disclose pagination behavior, sorting semantics, sentiment-analysis side effects, rate limits, authentication needs, or what a returned post contains.
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?
The description is a single clear sentence with no redundant wording or filler. It is well-structured and front-loaded, though it is arguably too sparse to add much value beyond the tool name.
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?
Given four parameters, no output schema, no annotations, and a large sibling-tool set, the description is incomplete. It does not explain return structure, pagination nuances, the optional sentiment feature, or how this differs from similar Facebook post tools.
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?
Schema description coverage is 100%, so every parameter is already documented in the input schema. The description adds no additional parameter meaning, but the baseline of 3 is appropriate because the schema handles parameter semantics.
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 a specific verb ('Get') and resource ('posts from a public Facebook group'). It distinguishes from page-related siblings by naming 'group', though it does not explicitly contrast with facebook_page_posts or search_facebook_posts.
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?
The 'public' qualifier is the only usage hint, implying private groups are not accessible. There is no guidance on when to prefer this tool over facebook_page_posts, facebook_post_comments, or search_facebook_posts, and no mention of prerequisites or alternatives.
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.