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mcp-TesouroDireto

mcp-TesouroDireto

by msperlin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_bond_stats

Read-only

Retrieve per-maturity summary statistics—last, minimum, maximum, mean yield and dates—for Brazilian government bonds to compare maturities without downloading full daily series.

Instructions

Summary statistics per bond maturity: last/min/max yield, mean and dates.

Returns JSON. Useful to compare many maturities without downloading the full
daily series.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_bond_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
end_dateNoOptional precise end date (YYYY-MM-DD).
last_yearNoLast calendar year. Defaults to the current year.
first_yearNoFirst calendar year (minimum 2005).
max_assetsNoMaximum number of maturities summarized (nearest maturities kept).
start_dateNoOptional precise start date (YYYY-MM-DD).
asset_codesNoBond families to include. Omit for all bonds.
force_downloadNoIgnore today's cached file and download again.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-data scope are covered. The description adds the comparison-oriented framing and return shape, but says nothing about caching or re-download cost even though a force_download parameter exists.

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

Conciseness4/5

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

Two short sentences with the core content front-loaded and no wasted clauses. 'Returns JSON' is slightly redundant given an output schema exists, which keeps it from a 5.

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

Completeness4/5

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

With an output schema covering return values and annotations covering safety, the description only needs to convey purpose and scope, which it does. The remaining gap is that it never explains the trade-off implied by max_assets or caching, though those are documented in the schema.

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 every parameter (dates, year range, max_assets, asset_codes, force_download) is already documented in the schema. The description adds no further meaning about how maturity selection or date ranges interact, so baseline 3 applies.

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?

States a specific verb+resource: summary statistics (last/min/max yield, mean, dates) per bond maturity. It implicitly separates itself from get_bond_data by noting it avoids 'downloading the full daily series', though it never names the sibling explicitly.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Useful to compare many maturities without downloading the full daily series' gives clear context for when to reach for this over the raw-data sibling. There are no explicit exclusions or prerequisites, which keeps it short of a 5.

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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