get_option_chainGet option chain metadata: available expirations and strikes for a ticker.
| 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 |
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, and the description's 'Get' aligns with this. It adds scope information (expirations and strikes) but does not detail return format or other behavioral aspects. With annotations covering the safety profile, this is an acceptable middle score.
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 a single, straightforward sentence that is front-loaded with the verb 'Get' and clearly specifies the resource and output. It is highly concise with no unnecessary 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?
Given the tool's low complexity, complete schema, and read-only annotation, the description sufficiently conveys that it returns expirations and strikes. No output schema exists, but the description offers enough detail for an agent to understand the tool's purpose and basic output.
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 both apiKey and symbol having clear descriptions. The tool description adds no additional parameter context, so the baseline score 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 states the tool retrieves option chain metadata, specifically available expirations and strikes for a ticker. This distinguishes it from sibling tools like get_option_quote or get_surface, which serve different purposes.
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: when you need expirations and strikes for a ticker. It provides clear context but does not explicitly mention when not to use it or name alternative tools. This meets the 'clear context, no exclusions' level.
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.