[Social Content] Search Eventbrite for upcoming events.
Args: query: Event topic (e.g. 'tech meetup', 'AI conference') location: City or region (e.g. 'San Francisco')
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| location | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true (safe read operation) and openWorldHint=true (no closed-world constraints). The description adds that it searches 'upcoming events,' which implies a temporal filter, but does not detail pagination, result limits, or sorting. No contradictions with annotations.
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 short (4 lines), starts with the core purpose, and clearly lists arguments with examples. No wasted words.
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?
No output schema exists, and schema coverage is 0%, so the description should explain return format or behavior. It states the tool searches for upcoming events but does not mention result count, pagination, or whether events are limited to a time range. Adequate for basic use but not fully 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?
Schema has 0% description coverage, so the description compensates by providing concrete examples for both parameters: 'query' as event topic (e.g., 'tech meetup') and 'location' as city/region (e.g., 'San Francisco'). This adds meaning beyond parameter names.
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 'Search Eventbrite for upcoming events,' identifying the source (Eventbrite) and action (search). This differentiates it from sibling tools like academic-research__search_arxiv or sales-intelligence__search_linkedin_jobs, which target different platforms.
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?
No explicit guidance on when to use this tool versus alternatives. While the name and domain (social-content) imply usage for event discovery, the description does not specify contexts where this is preferred or explain limitations (e.g., only upcoming events, no history).
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.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.