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LiveDataLink

options_chain

Read-onlyIdempotent

Get the options chain for a stock - calls and puts with strike prices, bid/ask spread, volume, open interest, implied volatility, and available expirations. Use this for "show me AAPL options", "what are the puts on Tesla?", "options expiring this Friday", "what's the implied volatility?", or any options trading question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by option type (default: "both")
symbolYesStock ticker symbol (e.g., "AAPL")
expirationNoExpiration date in YYYY-MM-DD format. Defaults to nearest expiration.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds useful output content context and examples but does not disclose behavioral details such as data freshness, pagination, snapshot timing, or whether all expirations are returned at once. It does not contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with the core action and return contents front-loaded, followed by concise example use cases. Every sentence earns its place with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple three-parameter schema, full parameter documentation, and safety annotations, the description is mostly complete: it states the resource, the data fields returned, and example queries. It does not explicitly address how this differs from the options_history_chain sibling, which is the main contextual gap, but the provided information is sufficient for an agent to invoke the tool correctly for a current options chain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each parameter already documented in the input schema. The description reinforces the meaning of type and expiration through examples but does not add substantial new semantic information beyond the schema. Baseline 3 is appropriate because the schema carries the parameter documentation burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: 'Get the options chain for a stock' and enumerates returned data such as strike prices, bid/ask spread, volume, open interest, implied volatility, and expirations. It is clear but does not explicitly contrast itself with sibling tools like options_history_chain or stock_quote, so it lacks direct sibling differentiation for a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit example user intents ('show me AAPL options', 'what are the puts on Tesla?', 'options expiring this Friday', 'what's the implied volatility?'), giving clear context for when to invoke the tool. It does not mention exclusions or alternative tools for historical options chains or other option-related tools, so it stops short of full when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.