Financial Modeling Prep (FMP) MCP Server

get_income_statement

Retrieve company income statements for financial analysis. Specify stock symbol and period (annual/quarterly) to access revenue, expenses, and profitability data.

Instructions

Get company income statement (annual or quarterly)

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": "get_income_statement"
  }
}

Input Schema

Name	Required	Description
`symbol`	Yes	Stock ticker symbol
`period`	No	Period type (annual or quarter)
`limit`	No	Number of periods to return (default: 5)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Mar 17, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't mention any behavioral traits like rate limits, authentication needs, data freshness, or what happens with invalid inputs. For a financial data tool with no annotation coverage, this 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 a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.

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

Completeness2/5

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

Given the complexity of financial data retrieval, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or data format, leaving gaps for an AI agent to understand how to use the tool effectively in context.

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%, so the schema already documents all parameters (symbol, period, limit) with descriptions and enums. The description adds minimal value by implying period options ('annual or quarterly'), which is already covered in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 tool's purpose: 'Get company income statement (annual or quarterly)'. It specifies the verb ('Get') and resource ('company income statement'), and distinguishes the period options. However, it doesn't explicitly differentiate from sibling tools like 'get_balance_sheet' or 'get_cash_flow', which are also financial statement tools.

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. It doesn't mention sibling tools like 'get_balance_sheet' or 'get_cash_flow' for other financial statements, nor does it specify prerequisites or contexts for choosing this tool over others in the server.

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