jp-statistics-mcp

get_series_data

Read-onlyIdempotent

Fetches observations for a single Bank of Japan (BOJ) time series from a specified database and period range, using YYYY or YYYYMM period formats.

Instructions

Fetch observations for one BOJ series. Periods are YYYY or YYYYMM by frequency.

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": {
      "database": "<database>",
      "series_code": "<series_code>",
      "start_period": "<start_period>",
      "end_period": "<end_period>"
    },
    "name": "get_series_data"
  }
}

Input Schema

Name	Required	Description	Default
`database`	Yes
`end_period`	Yes
`series_code`	Yes
`start_period`	Yes
`start_position`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 10, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so safety is covered. The description adds only the period-format constraint; it says nothing about what the underlying database holds, rate limits, or how start_position affects retrieval.

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?

Two short sentences with the core action front-loaded and no filler. Every clause carries information.

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?

The output schema removes the need to explain return values, and the period-format note covers the trickiest argument. However, with five parameters at 0% schema description coverage and an open-world database argument, the definition leaves real gaps for an agent assembling a call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning and it largely does not. It clarifies period granularity ('YYYY or YYYYMM by frequency'), which goes slightly beyond the regex, but says nothing about valid 'database' values, 'series_code' conventions, or what 'start_position' paginates.

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 (fetch) and resource (observations) scoped to exactly one BOJ series, which implicitly separates it from the sibling get_multiple_series_data. It stops short of explicitly naming or contrasting the alternatives.

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

Usage Guidelines3/5

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

The phrase 'one BOJ series' implies this is the single-series path versus the bulk siblings, but there is no explicit when-to-use/when-not guidance, no prerequisite about database codes, and no advice on choosing it over search_series or get_series_data_by_layer.

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

Deploy Server