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blpapi-mcp

blpapi-mcp

by djsamseng
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

earning

Retrieve Bloomberg earnings exposure for a ticker, segmented by geography or product categories with optional currency and level filters.

Instructions

Get Bloomberg earning exposure by Geo or Products

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": {
      "ticker": "<ticker>"
    },
    "name": "earning"
  }
}

Input Schema

NameRequiredDescriptionDefault
tickerYes
byNoGeo
typNoRevenue
ccyNo
levelNo
kwargsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'Get', implying a read operation, but does not confirm safety, side effects, rate limits, or return format. This is insufficient for an agent to understand behavioral implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise but lacks structure (e.g., no sections, bullet points). While brevity is positive, the significant under-specification reduces effectiveness.

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 has 6 parameters (1 required), no schema descriptions, no output schema, and no annotations, the description is vastly incomplete. An agent cannot reliably invoke this tool without additional information on parameter values, expected output, or usage constraints.

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 coverage is 0% (no parameter descriptions in schema), and the description adds almost no meaning to parameters. It mentions 'Geo or Products', which may relate to the 'by' parameter, but other parameters (ticker, typ, ccy, level, kwargs) are completely unexplained, leaving the agent to guess their semantics.

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 states the tool retrieves Bloomberg earning exposure, with a hint of breakdown by geography or products. This is specific enough to distinguish from sibling tools like bdh (historical data) or beqs (equity screening), but it does not explicitly compare or contrast.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when-not to use, or context for selection among the listed sibling tools.

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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