Skip to main content
Glama
jackdark425

Financial Modeling Prep (FMP) MCP Server

by jackdark425

get_analyst_estimates

Retrieve analyst financial estimates for stocks including revenue and EPS forecasts to support investment research and analysis.

Instructions

Get analyst financial estimates for a stock (revenue, EPS forecasts)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol
periodNoPeriod type (annual or quarter)
limitNoNumber of periods to return (default: 10)

Implementation Reference

  • The async handler function that executes the logic for 'get_analyst_estimates', fetching data from the FMP API.
    async (args: z.infer<typeof AnalystEstimatesSchema>) => {
      try {
        const period = args.period || 'annual';
        const limit = args.limit || 10;
        const data = await fetchFMP<AnalystEstimate[]>(
          `/analyst-estimates?symbol=${args.symbol.toUpperCase()}&period=${period}&limit=${limit}`
        );
        return jsonResponse(data);
      } catch (error) {
        return errorResponse(error);
      }
    }
  • The input validation schema (AnalystEstimatesSchema) for the 'get_analyst_estimates' tool.
    const AnalystEstimatesSchema = z.object({
      symbol: SymbolSchema.describe('Stock ticker symbol'),
      period: PeriodSchema.describe('Period type (annual or quarter)'),
      limit: LimitSchema.describe('Number of periods to return (default: 10)'),
    });
  • Registration of the 'get_analyst_estimates' tool within the server instance.
    server.registerTool(
      'get_analyst_estimates',
      {
        description: 'Get analyst financial estimates for a stock (revenue, EPS forecasts)',
        inputSchema: AnalystEstimatesSchema,
      },
      async (args: z.infer<typeof AnalystEstimatesSchema>) => {
        try {
          const period = args.period || 'annual';
          const limit = args.limit || 10;
          const data = await fetchFMP<AnalystEstimate[]>(
            `/analyst-estimates?symbol=${args.symbol.toUpperCase()}&period=${period}&limit=${limit}`
          );
          return jsonResponse(data);
        } catch (error) {
          return errorResponse(error);
        }
      }
    );
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 'Get[s]' data, implying a read-only operation, but doesn't mention other traits like authentication needs, rate limits, data freshness, or error handling. This is a significant gap for a tool with no annotation coverage.

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 that front-loads the core purpose. It avoids redundancy and wastes no words, making it easy to parse quickly.

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

Completeness3/5

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output format, leaving gaps that could hinder an AI agent's effective use.

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?

The schema description coverage is 100%, so the schema already documents all parameters (symbol, period, limit). The description adds minimal value beyond the schema, mentioning 'revenue, EPS forecasts' which hints at output content but doesn't clarify parameter usage or interactions. 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 analyst financial estimates for a stock (revenue, EPS forecasts)'. It specifies the verb ('Get'), resource ('analyst financial estimates'), and scope ('for a stock'), but doesn't explicitly differentiate it from sibling tools like 'get_analyst_ratings' or 'get_price_target', which might also relate to analyst data.

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_analyst_ratings' or 'get_price_target', which could be related, nor does it specify prerequisites or exclusions. Usage is implied only by the tool's name and description.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jackdark425/aigroup-fmp-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server