stat-gov-mcp
Related Servers
Alternatives to stat-gov-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceMCP server providing AI assistants access to Polish public registries (KRS, CEIDG) and statistical data (GUS BDL) for querying companies, sole proprietorships, and regional statistics.147MIT
- AlicenseAqualityCmaintenanceMCP server that provides AI agents with Polish business data tools: identifier validation (NIP, PESEL, REGON, KRS, IBAN), VAT whitelist checks, EU VIES lookups, and NBP exchange rates.58 npmMIT
- AlicenseNot gradedqualityCmaintenanceMCP server for accessing BPstat (Banco de Portugal) statistics API without API keys. Enables querying Portuguese central bank data through natural language.5 npmMIT
- AlicenseAqualityCmaintenanceProduction-grade MCP server for Statistics Finland's StatFin database. Enables AI assistants like Claude to browse, search, and query Finnish statistical data.711MIT
- AlicenseAqualityBmaintenanceMCP server for Eurostat statistics, enabling seamless search, query, and analysis of over 8,900 EU datasets with support for SDMX, DuckDB SQL, NUTS regional filtering, and CSV export.121MIT
- AlicenseNot gradedqualityCmaintenanceMCP server that enables querying Latvian official statistics from data.stat.gov.lv via PxWeb tables, allowing retrieval of table definitions and data through natural language or direct tool calls.4 npmMIT
TDQS
Scored across 5 tools
Each tool targets a clearly distinct entity or action: subjects, variables, units, unit details, and data. The descriptions cross-reference IDs and usage patterns, making it easy for an agent to select the right tool.
Tool names follow a consistent verb_noun pattern: search_subjects, search_variables, search_units, get_unit_details, get_data. All use lowercase snake_case and the prefixes search_ and get_ clearly distinguish discovery from retrieval.
Five tools is well-scoped for a statistical data access server. Each tool covers a necessary part of the browsing and data retrieval workflow without unnecessary or redundant additions.
The core workflow is complete: discover subjects, search variables, locate territorial units, get unit details, and fetch data. Minor gaps exist such as detailed variable metadata or subject detail endpoints, but they are not essential for typical data retrieval.