facebook_group_details
Get Facebook group details including name, description, members count, and privacy setting.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Facebook group URL |
Get Facebook group details including name, description, members count, and privacy setting.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Facebook group URL |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It only states 'Get', which implies a read-only operation, but provides no details about authentication requirements, rate limits, error behavior, or whether the group must be public. This lack of behavioral disclosure is a significant gap for a tool with no annotation support.
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 that immediately states the tool's purpose and key outputs. Every word earns its place, with no filler or redundancy.
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?
For a simple 1-parameter read tool, the description gives a fair overview but omits an exhaustive list of return fields (uses 'including'), and does not mention edge cases like invalid URLs or access restrictions. Given the absence of an output schema, the description is minimally viable but has clear gaps in behavioral and output completeness.
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?
The schema already provides 100% coverage by describing 'url' as 'Facebook group URL'. The description adds no extra meaning about the parameter, such as URL format or validation rules. Since schema coverage is high, the baseline is 3, and the description does not exceed that.
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 uses the specific verb 'Get' with the resource 'Facebook group details' and explicitly lists the key attributes returned (name, description, members count, privacy setting). This clearly distinguishes it from sibling tools like facebook_page_details or facebook_group_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?
There is no guidance on when to use this tool versus alternatives. It does not mention scenarios where this tool is appropriate (e.g., retrieving metadata for a specific group) or when to prefer sibling tools like facebook_group_posts. No exclusions or alternative recommendations are provided.
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.