Search Google Finance by keyword to find matching instruments and retrieve ticker, exchange, company, currency, price, change, and percentage change in one JSON response.
Google Finance Search API. Searches Google Finance for instruments matching q, such as a company name. Each match has its ticker, exchange, company name, currency, price, change and percentage change.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Keyword to search for (e.g., Apple) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It helpfully enumerates the return fields (ticker, exchange, company name, currency, price, change, percentage change), which is valuable given there is no output schema, but it says nothing about auth requirements, rate limits, result count, or pagination.
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?
Three short sentences, front-loaded with the operation and immediately stating the search key. The opening 'Google Finance Search API' is mildly redundant with the tool name, but the return-field sentence earns its place given no output schema exists.
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 one-parameter search tool with no annotations and no output schema, the description covers the input and outlines the return shape, which is adequate. It lacks any usage context or sibling differentiation, leaving a gap for an agent choosing among the many google_finance_* tools.
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 coverage is 100% and the schema already documents q as 'Keyword to search for (e.g., Apple)'. The description's 'such as a company name' adds only marginal meaning over the schema, so the baseline 3 applies.
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?
States a specific verb and resource – 'Searches Google Finance for instruments matching q' – and clarifies the match type with a company-name example. It is clear about what the tool does, but does not distinguish itself from closely related siblings like google_finance_quote, google_finance_ticker, or google_finance_company.
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?
There is no when-to-use guidance, no mention of prerequisites, and no routing to alternatives such as google_finance_quote or google_finance_company. The agent must infer the appropriate context entirely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.