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shop-mcp

by ablinovsibset-spec
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Python
Remote

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    Related Servers

    • shop-db

      alser15
      F
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      This MCP server lets an AI agent securely connect to a read-only SQLite store database, inspect its tables and schema, and run analytical SQL queries without modifying any data.
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    • mcp-data-analyst

      flashgari
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      A natural-language data analyst MCP server that lets users query SQLite sales datasets via MCP tools (list_tables, aggregate, time_series, run_sql) with read-only SQL safety guards, returning results through a FastAPI dashboard.
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    • Shop Analytics MCP Server

      bogdaamn
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      Enables AI agents to answer analytical questions about an online store's SQLite database through specialized read-only tools, without any risk of modifying the underlying data.
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    • Shop SQLite MCP

      mixe-deep
      F
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      quality
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      Enables safe, read-only analysis of an online store's SQLite database, providing schema introspection, restricted SELECT queries, and specialized analytics tools through MCP.
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    • MCP SQLite RBAC Demo

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    • Shop Database MCP Server

      slavamirgit
      F
      license
      Not graded
      quality
      C
      maintenance
      This server lets AI agents discover a SQLite shop database schema, compose read-only analytical SQL, and determine which questions the database cannot answer.
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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

    A4.2/5.0

    Scored across 8 tools

    Disambiguation3/5

    Most tools are clearly distinct, but count_customers_by_country and rank_countries_by_customers return the same country-level customer counts with only ordering/filtering differences. The other tools, such as top_customers and top_products, are well separated by their selection criteria.

    Naming Consistency4/5

    Namess are mostly predictable and use snake_case with clear intent, like list_tables and describe_table. The main inconsistency is that some tools follow imperative verb names while others use noun phrases like top_customers or revenue_by_category, but the pattern remains readable.

    Tool Count5/5

    Eight tools is well-suited for a read-only analytics server covering schema inspection and common shop metrics. Each tool has a clear role, and the count does not feel excessive or thin.

    Completeness4/5

    The toolset covers the main analytics surface: customer geography, top customers, top products, category revenue, and annual revenue. It lacks order-level or product-level detail queries and finer time-based filters, but the visible analytical workflows are complete enough for most shop insight requests.

    Maintenance

    ActivityMaintained
    ResponsivenessResponsive

    Resources