Get the full profile for a single Threads (Meta's Threads app) user by username. Returns biography, bio links, follower count, verification status, and profile metadata. Billed $0.006 per request.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | Threads username, with or without leading @ (max 100 characters) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It adds useful context by listing the returned data fields and the billing cost per request. However, it does not disclose potential rate limits, authentication requirements, or any error behavior. For a read-only profile fetch, the return-value list is helpful but incomplete for full behavioral transparency.
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 two sentences, front-loaded with the core purpose, followed by a concise list of return fields and the billing detail. Every sentence adds value without redundancy or fluff. It is highly scannable and appropriately sized for a simple tool.
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 the tool's simplicity (one parameter, no output schema), the description provides a complete enough overview: it states the purpose, the key return fields, and even billing cost. It does not explicitly note the absence of posts or recent activity, which could help distinguish from sibling tools, but that is a minor gap. The absence of an output schema is compensated by listing the main fields.
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 input schema is fully described (coverage 100%), with 'username' having a clear description ('Threads username, with or without leading @'). The tool description adds minimal extra meaning beyond saying 'by username', which is already evident. Since the schema already provides strong semantics, the description neither enhances nor detracts significantly, earning the baseline score of 3.
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 a specific verb ('Get') and clearly identifies the resource ('full profile for a single Threads user by username'). It lists key return fields (biography, bio links, follower count, verification status), which distinguishes it from sibling tools like threads_user_posts or search_threads_users. The purpose is unambiguous and action-oriented.
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 description clearly implies usage context: when you need a full profile for a specific Threads username. It does not explicitly state when not to use it or mention alternatives, but the phrasing 'single Threads user by username' inherently distinguishes it from search tools and post-focused tools. No exclusions are provided, but for a simple lookup this is adequate.
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.
