Get historical daily stock prices (OHLC). Returns a summary by default; set series=true to get the full daily price series (for backtesting / charting).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max rows of the daily series to return when series=true. | |
| period | No | Look-back window | 1y |
| series | No | If true, return the full daily OHLC series (up to `limit` rows) instead of just a summary. | |
| ticker | Yes | Stock ticker symbol |
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?
No annotations are provided, so the description carries the full burden. It discloses two modes (summary and full series) and ties the series parameter to returning 'full daily price series', but does not detail what the summary contains or any other behavioral traits like rate limits or data range.
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?
Two sentences: first states purpose, second explains the two modes. No clutter, front-loaded with key information.
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?
With no output schema, the description doesn't explain the return format of the summary or series. However, given the low complexity and clear parameter descriptions, it covers the essential usage. A slight gap remains for output details.
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%, but the description adds meaning by explaining that 'series' controls summary vs. full series and that 'limit' and 'period' apply when series=true. This goes beyond the schema's parameter descriptions.
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 'Get historical daily stock prices (OHLC)' with a specific verb and resource. It distinguishes between summary and full series modes, and no sibling tool overlaps this functionality.
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 explains when to use the default vs. series=true ('for backtesting / charting'). It does not explicitly mention when not to use this tool or alternatives, but sibling tools cover different domains, making context sufficient.
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 and action, and descriptions explicitly disambiguate similar pairs (e.g., get_congress_member vs get_congress_trades, get_crypto_holder vs get_crypto_holders). No two tools appear to do the same thing.
The dominant pattern is get_<noun>, with list_<noun> for enumerations. Minor deviations exist: a bare 'search' tool and the 'sec_' prefix on SEC filing tools break the uniform verb_noun style, but the pattern remains predictable.
At 24 tools, this is on the heavier side, but the server spans multiple financial data domains (SEC filings, stocks, insider trading, crypto, rates, economics), so each tool has a clear purpose. It is just below the 'too many' threshold.
The tool surface is remarkably complete for financial data retrieval: SEC filing lifecycle is covered (list -> index -> document), institutional ownership is available from both stock and institution perspectives, and insider/congress/crypto/economic data are all present. No obvious gaps or dead ends.