get_vexGet vanna exposure (VEX) by strike. Shows how dealer hedging changes with volatility moves.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | No | FlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp. | |
| symbol | Yes | Stock/ETF ticker | |
| expiration | No | Optional expiration date YYYY-MM-DD |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / apiKey / defaultAdded value: +nullInput schema / properties / apiKey / descriptionPrevious value: -"Your FlashAlpha API key"New value: +"FlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp."Input schema / properties / apiKey / typePrevious value: -"string"New value: +[
+ "string",
+ "null"
+]Input schema / requiredPrevious value: -[
- "symbol",
- "apiKey"
-]New value: +[
+ "symbol"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds interpretive context about what VEX measures, but does not disclose behavioral traits like output format, pagination, or data granularity. It adds some value beyond annotations but not rich behavioral detail.
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, front-loaded with the purpose, and no wasted words. The first sentence states the action and target; the second clarifies the metric's meaning. Extremely concise and well-structured.
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 read-only data tool with good annotations and full schema descriptions, the description is largely sufficient. It lacks an output schema and does not explicitly describe the return shape, but the phrase 'by strike' implies a list of strikes with VEX values. This is a minor gap in an otherwise complete description.
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 100%, with each parameter (apiKey, symbol, expiration) already explained. The description adds no additional parameter semantics beyond mentioning 'by strike', which is implied but not a parameter-level detail. Baseline 3 is appropriate when the schema carries the full burden.
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 uses a specific verb ('Get') and resource ('vanna exposure by strike'), and adds a clarifying definition ('shows how dealer hedging changes with volatility moves'). This clearly differentiates it from sibling exposure tools like get_gex or get_dex.
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 clear context on when to use this tool (to obtain vanna exposure by strike and understand dealer hedging reactions to volatility moves), but does not explicitly mention alternatives or exclusions, such as using get_historical_vex for historical data.
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 scopes: get_stock_summary, get_volatility, get_vrp, and get_exposure_summary all return comprehensive analytics with shared metrics, making it hard to pick the right one. The flow family (get_flow_live, get_flow_summary, get_flow_scan, get_flow_signals, etc.) has significant redundancy — get_flow_live bundles data also available via separate tools.
Tool names mostly follow a consistent get_<noun> pattern, with clear subgroups like get_historical_* and get_*_exposure. Minor deviations exist: post_screener, post_structure_pnl, calculate_greeks, and solve_iv break the get_ convention, but they are still predictable and readable.
With 73 tools, this is far beyond the 3–15 tool sweet spot and even the 50+ extreme mismatch threshold. While the domain is broad, the enormous surface is bloated by near-duplicate historical replay variants (18 get_historical_* tools) and multiple overlapping summary endpoints, making it unwieldy for an agent.
The tool set provides thorough coverage of options analytics: quotes, chains, greeks, volatility surface, VRP, exposure, flow, historical replay, screening, and strategy analysis. There are no obvious dead ends — core workflows like calculating greeks, getting exposure, and screening the universe are all supported.