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Alpha Vantage MCP Server

Alpha Vantage MCP Server

by calvernaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

historical_options

Retrieve historical options data for specific stock symbols to analyze past market behavior and inform trading strategies.

Instructions

Fetch historical options

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "historical_options"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolYes
datatypeNo
contractNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.7/5.0
Behavior1/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states the action ('fetch') without details on permissions, rate limits, data format, or side effects. For a tool with no annotations and three parameters, this is inadequate and fails to inform the agent about how the tool behaves.

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 extremely concise with just two words, 'Fetch historical options', which is front-loaded and wastes no space. However, this brevity comes at the cost of clarity and completeness, but as a standalone text, it's efficiently structured.

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

Completeness1/5

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

Given the tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It lacks purpose differentiation, usage guidelines, behavioral details, and parameter explanations. For a data-fetching tool in a financial context, this minimal description fails to provide necessary context for effective use.

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

Parameters1/5

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

Schema description coverage is 0%, meaning parameters 'symbol', 'datatype', and 'contract' are undocumented in the schema. The description adds no meaning about these parameters—it doesn't explain what they represent, their formats, or examples. With low coverage and no compensation, this leaves parameters ambiguous.

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

Purpose2/5

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

The description 'Fetch historical options' states a verb ('fetch') and resource ('historical options'), but it's vague about what 'historical options' means—likely financial options data, but this isn't specified. It doesn't distinguish from siblings like 'realtime_options' or 'company_overview', leaving ambiguity. This is a tautology that mostly restates the tool name without added clarity.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives. With siblings like 'realtime_options' and 'time_series_daily', the description offers no context on use cases, prerequisites, or exclusions. This leaves the agent without direction for selection.

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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