finnhub_quoteReal-time quote for a stock — current price (c), change (d), percent change (dp), high (h), low (l), open (o), previous close (pc) and unix timestamp (t). Finnhub REST: GET /quote.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | Stock ticker symbol, e.g. 'AAPL' (required). |
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?
The readOnlyHint annotation already signals a safe read operation, and the description adds value by listing the exact response fields and the REST endpoint. It discloses the output structure (c, d, dp, h, l, o, pc, t), which is useful behavioral context beyond the annotation.
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, front-loaded with the core purpose, and contains no filler. It lists output fields in a compact format and includes the endpoint reference, making every sentence informative.
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 quote tool with one parameter and read-only annotations, the description is complete. It explains the return fields, which is especially important since there is no output schema, and provides the REST endpoint for further reference.
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 schema fully documents the single parameter 'symbol' with a clear description and example, so the schema carries the semantic weight. The tool description adds no additional parameter-level information, but it doesn't need to given 100% schema coverage.
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 provides a real-time quote for a stock and enumerates the returned fields (current price, change, percent change, etc.), making its purpose specific and unambiguous. This distinguishes it from sibling tools like company_news or market_status, which address different Finnhub endpoints.
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 offers clear context by indicating this is for real-time stock quotes, which implies the right use case. However, it does not explicitly mention when not to use it or point to alternative tools for related but distinct data needs, such as historical data or detailed financials.
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 resource or data type (company profile, news, earnings, insider transactions, quotes, etc.). The two news tools (company_news vs market_news) and the two earnings tools (calendar vs surprises) are clearly differentiated by description, leaving no ambiguity for an agent.
All tool names follow a consistent pattern: the `finnhub_` prefix followed by a lowercase snake_case noun phrase (e.g., `finnhub_company_news`, `finnhub_market_status`). This uniform naming convention makes tool selection predictable.
With 15 tools, the set is well-scoped for a financial data server, covering a broad range of endpoints without unnecessary bloat. Each tool has a clear purpose and corresponds to a meaningful Finnhub API endpoint.
The tool set covers core financial data needs: company profile, financials, news, earnings, quotes, recommendations, and market status. Minor gaps exist, such as lack of historical price candles or full financial statements, but these are not critical for the apparent server purpose and most workflows are supported.