No-key stock quote data via Stooq. Accepts comma-separated ticker symbols and returns quote/OHLC/volume observations with timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Ticker symbol(s) e.g. 'AAPL' or 'MSFT,GOOG' |
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?
Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds value by disclosing the data source (Stooq), the lack of an API key requirement, and the output format (quote/OHLC/volume with timestamps). It does not contradict the 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 two succinct sentences that front-load the core value proposition ('No-key stock quote data via Stooq') and then explain input and output. 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?
For a simple one-parameter tool, the description covers purpose, input, and output format. It does not describe data granularity, timezone, or limitations, but these are not critical given the tool's simplicity and the absence of an output schema. The return value description is sufficient.
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 has a single parameter 'url' with a description clarifying it expects ticker symbols. The description echoes the comma-separated format but does not add additional parameter semantics beyond the schema. With 100% schema coverage, the baseline of 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 clearly identifies the tool's function: retrieving stock quote data from Stooq without an API key. It distinguishes itself from the sibling extract_finance_landscape by focusing on quote/OHLC/volume data rather than broader company landscape. The verb 'extract' is implicit in the name, but the description explicitly states it 'returns' data.
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 implies usage for stock quote retrieval but does not explicitly state when to use this tool over alternatives like extract_finance_landscape. It lacks exclusions or comparative guidance. The 'No-key' mention is a distinguishing feature but not a usage guideline.
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.
Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.
Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.
11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.
The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.