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Alpha Vantage MCP Server

Alpha Vantage MCP Server

by calvernaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

balance_sheet

Fetch company balance sheet data from Alpha Vantage to analyze financial position, assets, liabilities, and equity for investment research.

Instructions

Fetch company balance sheet

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": "balance_sheet"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.5/5.0
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 the description doesn't specify whether this requires authentication, has rate limits, returns real-time or historical data, or what format the balance sheet data comes in. This leaves critical behavioral traits undocumented.

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 at just three words, front-loading the core purpose without any wasted language. Every word earns its place, though this conciseness comes at the cost of completeness.

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?

For a financial data tool with no annotations, no output schema, and 0% schema parameter coverage, the description is completely inadequate. It doesn't explain what data is returned, how to interpret results, or any operational constraints, leaving the agent with insufficient context to use the tool effectively.

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?

With 0% schema description coverage for the single parameter 'symbol', the description provides no additional meaning about what 'symbol' represents (e.g., stock ticker, company identifier), expected format, or examples. The description doesn't compensate for the schema's lack of documentation.

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 the verb 'fetch' and the resource 'company balance sheet', making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'income_statement' or 'cash_flow', which would require more specific language about what distinguishes a balance sheet from other financial statements.

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

Usage Guidelines2/5

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 like 'income_statement' or 'cash_flow', nor does it mention any prerequisites or context for usage. It simply states what the tool does without indicating appropriate scenarios.

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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