Skip to main content
Glama

Stat Ee

by io.github.pipeworx-io

Subjects

subjects
Read-onlyIdempotent

Browse Statistics Estonia (Statistikaamet) official ESTONIA national statistics — the subject tree of available tables, one level at a time. Items are type "l" (folder) or "t" (table, id ends in .px). Handy for listing everything under a path you already know; to go straight from an English question ("average monthly wage in Estonia") to a table path in one call, use stat_ee_find_table. Follow either with table_meta + query_table to pull the actual figures.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoSub-path under /stat/ (default empty = root). e.g. "rahvastik/rahvastikunaitajad-ja-koosseis"

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "path": ""
+  },
+  {
+    "path": "rahvastik/rahvastikunaitajad-ja-koosseis"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only and safety, so the description adds context beyond that: items are type 'l' or 't', ids end in .px, and browsing is 'one level at a time.' This gives a partial sense of the return structure, though no output schema exists. No annotation contradiction.

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 sentences, front-loaded with the tool's purpose and then adding usage guidance. No redundant words, every sentence earns its place.

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

Completeness5/5

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

For a simple browse tool, the description covers the core behavior, return item types, and workflow integration with sibling tools. It adequately fills the gap left by the absent output schema and makes the tool usable in a larger context.

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?

The schema description for the single parameter 'path' is already detailed (sub-path under /stat/, default empty, example). The description only reinforces the use of a path, so it adds no new meaning beyond the schema. Baseline 3 applies for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'browse[s] the subject tree of available tables' with a specific verb and resource. It distinguishes itself from the sibling stat_ee_find_table by noting that this tool is for browsing a known path while the sibling handles English questions. This makes the purpose unambiguous.

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

Usage Guidelines5/5

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

It explicitly says when to use this tool: 'Handy for listing everything under a path you already know' and provides an alternative ('use stat_ee_find_table'). It also gives follow-up steps with table_meta + query_table, so usage is well-defined.

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

All Stat Ee toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation3/5

Most tools have fairly distinct action/resource targets and the descriptions carefully separate entry points like ask_pipeworx, deep_research, and ask_pipeworx_grounded. However, ask_pipeworx_beta is explicitly an identical clone of ask_pipeworx right now, and a few related pairs (ai_visibility_check vs scan_competitor_ai_presence, stat_ee_find_table fetch_latest vs estonia_average_wage) add ambiguity.

Naming Consistency3/5

Names are consistently lowercase snake_case and verb-led names like resolve_entity, query_table, and suggest_questions are clear. But the set mixes conventions: bare nouns (subjects, recall, forget), adjective-noun phrases (recent_alerts, recent_changes), no-verb names (estonia_average_wage, table_meta), and multiple prefixes (pipeworx_*, polymarket_*, stat_ee_*). It is readable but not a single predictable pattern.

Tool Count2/5

36 tools is well above the 15-tool threshold for a well-scoped server, and the set spans many unrelated domains: Estonian statistics, Pipeworx research, Polymarket betting, AI visibility, npm scanning, memory, and subscriptions. There is also clear redundancy (ask_pipeworx_beta duplicates ask_pipeworx, ai_visibility_check could be folded into scan_competitor_ai_presence). This feels scattered for a server named 'Stat Ee'.

Completeness4/5

For the broad data-research/agent-assistant purpose, key workflows are well covered: discovery/query/grounded/deep research, entity resolution/profile/compare/validate/recent changes, complete memory CRUD, subscription CRUD with alert feeds, and a full Polymarket edge/arb/fill-risk suite. The main gap is not missing operations within these workflows but rather the overall scope being too broad and unfocused.

Resources