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Alpha Vantage MCP Server

Alpha Vantage MCP Server

by calvernaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

sma

Calculate simple moving average for stocks using Alpha Vantage data to analyze price trends and identify market signals.

Instructions

Fetch simple moving average

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>",
      "interval": "<interval>",
      "time_period": "<time_period>",
      "series_type": "<series_type>"
    },
    "name": "sma"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolYes
intervalYes
monthNo
time_periodYes
series_typeYes
datatypeNo
max_data_pointsNoMaximum number of data points to return (default: 100)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.8/5.0
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fetch' implies a read operation, but it doesn't describe authentication needs, rate limits, data freshness, error conditions, or output format. For a financial data tool with 7 parameters, this lack of behavioral context is a significant gap.

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 three words, front-loaded and zero waste. It efficiently states the core function without unnecessary elaboration, making it easy to parse quickly.

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 complexity (7 parameters, low schema coverage, no annotations, no output schema, and many sibling tools), the description is incomplete. It doesn't cover usage context, parameter meanings, behavioral traits, or output expectations, making it inadequate for effective tool selection and invocation.

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

Parameters2/5

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

Schema description coverage is low at 14%, with only one parameter ('max_data_points') having a description. The tool description adds no parameter information beyond the name 'sma', failing to explain what 'symbol', 'interval', 'time_period', etc., mean or their expected values. This leaves most parameters undocumented.

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 simple moving average' states the action ('fetch') and resource ('simple moving average'), but it's vague about scope and context. It doesn't specify what type of data (e.g., stock prices, commodities) or differentiate from similar sibling tools like 'ema' (exponential moving average) or 'wma' (weighted moving average). The purpose is identifiable but lacks specificity.

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?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for technical indicators (e.g., 'ema', 'wma', 'rsi'), there's no mention of when a simple moving average is preferred, what prerequisites exist, or any exclusions. This leaves the agent without context 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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