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649,985 tools. Updated 2026-10-10 23:42

"DuckDB" matching MCP tools:

  • Check the installed DuckDB version to determine available features and ensure compatibility with your SQL queries.
    MIT
  • Execute SQL queries against MotherDuck or DuckDB databases directly from your AI assistant or IDE. Analyze data with DuckDB SQL dialect efficiently.
    MIT
  • Get table column details including DuckDB types, nullability, null counts, and sample values to understand data structure and quality.
    MIT

Matching MCP Servers

  • A
    license
    A
    quality
    B
    maintenance
    Enables read-only SQL querying and exploration of data files (CSV, Parquet, JSON, Excel, etc.) via DuckDB, supporting local paths, globs, URLs, and S3 buckets.
    5
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.
    12
    MIT
  • Execute SQL queries on DuckDB databases to retrieve, analyze, or modify data stored locally, in memory, or in the cloud.
    MIT
  • Run SQL queries directly on DuckDB databases to retrieve, manipulate, and analyze data.
    MIT
  • Execute SQL queries on DuckDB databases to retrieve, filter, and manipulate data. Directly interact with the database for analysis and exploration.
    MIT
  • Run SQL queries on DuckDB or MotherDuck databases. Unqualified table names resolve automatically to the current database and schema.
    MIT
    Destructive
  • List all databases in the current connection to view attached DuckDB or MotherDuck databases. Useful when multiple databases are attached.
    MIT
  • Show all tables and views with their comments from a specified or current database. Filter by schema to explore MotherDuck or DuckDB data.
    MIT
  • List all configured database connections to discover available options and select one for use. Returns connection names, types, and details without exposing passwords.
    Apache 2.0
  • Check a semantic layer project for correctness across parse, runtime, examples, tests, and release modes to catch errors before trusting analytics answers.
    Apache 2.0
  • Join two spatial datasets using intersects, within, or contains predicates, with automatic engine selection and warnings for empty or non-overlapping results.
    AGPL 3.0
  • Inspect installed Australian legal data modules: version, jurisdiction, document counts, load status, snapshot date, and staleness. Optionally view refused modules with failure reasons.
    Apache 2.0
  • Search Australian legislation and case law with natural-language queries; uses local embeddings to rank results by semantic relevance.
    Apache 2.0
  • Resolves a specific provision of an Australian Act or instrument by its citation, returning the provision text with provenance from installed local data modules.
    Apache 2.0