[Finance & Markets] Screen stocks using Finviz stock screener. Filter by market cap, sector, PE ratio, and other financial metrics.
Args: screener_url: Finviz filter URL or criteria (e.g. "cap_large,sec_technology" for large-cap tech stocks) max_results: Maximum number of results (default 20)
| Name | Required | Description | Default |
|---|---|---|---|
| max_results | No | ||
| screener_url | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond the annotations. Annotations already indicate readOnlyHint=true and openWorldHint=true, which the description does not contradict. It mentions the source (Finviz), but does not disclose additional traits like rate limits, result format, or typical behavior.
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 concise, starting with a clear category header, followed by a brief purpose statement, and then parameter details. Every sentence adds value without unnecessary fluff.
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?
The description lacks important details such as what the tool returns (e.g., a list of tickers, full stock data, or a table). With no output schema, this omission reduces completeness. Also, it does not specify the market scope (e.g., US equities) despite similar sibling tools for global markets.
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 0%, so the description carries full responsibility. It provides clear explanations for both parameters, including an example for 'screener_url' (e.g., 'cap_large,sec_technology'). This adds significant value beyond the bare schema.
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 the tool screens stocks using Finviz stock screener and lists example filters. It distinguishes from sibling tools like 'finance__get_stock_data' by focusing on screening rather than retrieving specific stock data. However, it does not explicitly differentiate from other Finviz-based screeners.
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 provides no guidance on when to use this tool versus alternatives, such as the global-equities-screener tools for specific markets. It lacks comparison or context for choosing this tool over others.
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.