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blpapi-mcp

blpapi-mcp

by djsamseng
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

turnover

Calculates adjusted turnover in millions for specified tickers, with optional date range and currency conversion.

Instructions

Calculate the adjusted turnover (in millions)

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": {
      "tickers": "<tickers>"
    },
    "name": "turnover"
  }
}

Input Schema

NameRequiredDescriptionDefault
tickersYes
fldsNoTurnover
start_dateNo
end_dateNo
ccyNoUSD
factorNo

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?

With no annotations, the description should disclose behavioral traits (e.g., whether it is read-only, permissions needed, rate limits). It only states a calculation, omitting any such details.

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 sentence, which is concise, but it sacrifices necessary detail. It could include structured information about parameters without being verbose.

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, no annotations, and no output schema, the description is severely incomplete. It fails to explain the return format, parameter interactions, or how to properly invoke the tool.

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?

The description adds no meaning to the parameters. Schema coverage is 0%, yet the description does not mention tickers, flds, dates, ccy, or factor, leaving their roles entirely unclear.

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 calculates adjusted turnover and notes output is in millions. However, it does not differentiate from sibling tools like bdp or bdh, which may also provide turnover-related 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 lacks context about prerequisites, typical use cases, or when not to use it.

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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