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io.github.rubatoyd/kosis-openapi-mcp

by rubatoyd
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Python
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    • kosis-kr

      pipeworx-io
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      Enables browsing, searching, and pulling time series from Statistics Korea's KOSIS database, covering ~100,000 tables on population, prices, employment, trade, and industry.
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    • korea-bok-stats-mcp

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      Enables querying Bank of Korea ECOS economic statistics via Open API, including searching tables, retrieving time series data, and accessing key indicators.
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    • Korea Stats MCP

      Dayoooun
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      Enables natural language querying of Korean statistical data from KOSIS, including population, employment, GDP, housing prices, and more, with support for regional and trend analysis.
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    • kosis-mcp

      updown256
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      Enables querying Korean official statistics from KOSIS via natural language in MCP clients like Claude Desktop, wrapping the KOSIS OpenAPI for search, data retrieval, and metadata exploration.
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    • Korean Stats MCP

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      Enables AI assistants to retrieve real-time official Korean statistics from the KOSIS database through natural language queries, with source citations.
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool has a single clear role: table search vs indicator search, table data vs indicator data, metadata vs survey explanation, data retrieval vs file export. The detailed descriptions explicitly distinguish the similar indicator/table families, so an agent can reliably choose between them.

    Naming Consistency4/5

    All tools share the kosis_ prefix and snake_case, and the search/data pairs are parallel (kosis_search/kosis_indicator_search, kosis_data/kosis_indicator_data). However, the second part mixes bare verbs (search, list, explain, collect) with bare nouns (meta, data, citation, guide), so it is not a strict verb_noun convention.

    Tool Count5/5

    11 tools is well within the ideal range and each one earns its place: status/guide for orientation, search/explain/list/meta/data for the table workflow, indicator_search/indicator_data for the indicator workflow, plus collect and citation for output and scholarship.

    Completeness5/5

    For a read-only statistical data API, the surface is complete: users can discover tables by search or tree, read survey descriptions and table metadata, fetch full table data with automatic axis/period handling, access major indicators, export to files, and generate citations. No obvious dead ends or missing core operations remain.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources