search_statsSearch e-Stat statistical tables. Returns IDs and names for tables matching the query. Use the IDs with get_data / get_metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | J (Japanese, default) | E (English) | |
| limit | No | 1-100000 (default 20) | |
| query | Yes | Free-text (Japanese or English) | |
| start_position | No | 1-based row offset (default 1) |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "query": "失業率"
+ },
+ {
+ "lang": "E",
+ "limit": 10,
+ "query": "unemployment rate"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Response from e-Stat getStatsList endpoint containing search results",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds that it returns IDs and names, providing useful behavioral context beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first defines purpose, second provides usage guidance. No redundant words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with an output schema, so description need not detail return values. It covers what is returned (IDs and names) and how to use them, which is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for all 4 parameters. The description does not add extra parameter details beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches e-Stat statistical tables and returns IDs and names, with specific verb and resource. It also distinguishes from sibling tools get_data and get_metadata by directing to use the IDs with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to find statistical tables) and references get_data/get_metadata as follow-up, but lacks explicit when-not-to-use or contrast with other search tools like deep_research.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, especially the ask_pipeworx variants and Polymarket tools, but detailed descriptions help differentiate. Some tools like 'discover_tools' and 'suggest_questions' also have similar discovery roles, causing potential confusion.
Names follow snake_case but lack a consistent pattern: some start with verbs (e.g., 'ask_pipeworx', 'compare_entities'), others with nouns (e.g., 'entity_profile', 'recent_changes'), and prefixes like 'pipeworx_' and 'polymarket_' are used sporadically, making the naming scheme mixed but still readable.
35 tools is excessive for a server named 'Estat Japan', which should focus on Japanese statistics. The majority of tools are general-purpose Pipeworx tools, diluting the scope and making the count feel bloated for the stated purpose.
The e-Stat tools (list_data_catalog, search_stats, get_metadata, get_data) provide basic read-only access but lack update or delete operations. The inclusion of many unrelated tools leaves significant gaps for Japanese statistics, and the overall surface is incomplete for the server's implied domain.