Get detailed information about a LinkedIn company page by URL. Returns company name, description, employee count, locations, specialities, industry, website, and similar companies.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | LinkedIn company page URL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It lists the exact return fields, which is useful, but it does not disclose potential failure scenarios (e.g., invalid URL, missing data) or whether any special permissions are required. The behavior is a simple read, but edge cases are not addressed.
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, front-loaded sentence that directly states the action and lists the return fields. Every word contributes to understanding, with no redundancy or unnecessary detail.
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 tool with one parameter and no output schema, the description adequately covers input (URL) and output (specific fields). It does not mention error handling or the need for prior search, but given the low complexity, the description is sufficiently complete.
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 already provides 100% coverage for the url parameter with a description ('LinkedIn company page URL'). The tool description merely repeats 'by URL' without adding extra meaning, such as URL format examples or constraints. Since schema fully documents the parameter, baseline 3 is appropriate.
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 explicitly states 'Get detailed information about a LinkedIn company page by URL' and enumerates the specific fields returned (name, description, employee count, etc.). This clearly distinguishes it from siblings like linkedin_company_posts (posts) and search_linkedin_companies (search).
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 the use case: you need a LinkedIn company URL to retrieve detailed metadata. It mentions the URL requirement but does not explicitly contrast with alternatives such as search_linkedin_companies or note when not to use the tool. Context is clear, but exclusions are missing.
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.
