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443,740 tools. Updated 2026-08-11 14:13

"DuckDB" matching MCP tools:

  • Run SQL queries directly on DuckDB databases to retrieve, manipulate, and analyze data.
    MIT
  • Execute SQL queries against MotherDuck or DuckDB databases directly from your AI assistant or IDE. Analyze data with DuckDB SQL dialect efficiently.
    MIT
  • Execute SQL queries on DuckDB databases to retrieve, analyze, or modify data stored locally, in memory, or in the cloud.
    MIT
  • List all configured database connections to discover available databases and choose which connection to use. Ideal when connection name is unknown.
    Apache 2.0
  • Execute SQL queries to retrieve, insert, update, or delete data from a connected database. Supports parameterized inputs for secure querying.
    Apache 2.0

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
    C
    maintenance
    A read-only DuckDB MCP server offering context-efficient analytics tools (list_datasets, describe_table, profile_column, explain, query) with a semantic layer for business rules, security guards, and disclosed truncation to help LLMs produce correct answers while minimizing token usage.
    5
    MIT
  • Execute data quality validation rules from a YAML file against DuckDB, BigQuery, Athena, Databricks, or Postgres, returning a JSON report with optional LLM-driven root cause analysis.
    Apache 2.0
  • Inspect or query remote tabular files (Parquet/CSV/TSV) without downloading. Use schema, preview, head, SQL, or profile operations.
    MIT
  • Discover all available tables in the warehouse with row counts, grain, and business rule caveats to know what data you can query before writing SQL.
    MIT
  • Execute read-only SELECT statements against a DuckDB warehouse to fetch row results, with enforced limits and clear truncation notices.
    MIT
  • Run read-only SQL queries on cached open data resources, including CSV, TSV, XLSX, JSON, and ODS files. Supports SELECT statements with row limits for safe analysis.
    MIT
  • Run read-only SQL queries across CSV, Parquet, and JSON files, with JOIN support and capped results.
    MIT
  • Execute read-only SQL queries on data files (CSV, Parquet, JSON, Excel) to explore and return results as markdown tables.
    MIT
  • Retrieve column names, inferred data types, and sample values from a dataset file to understand its structure before running further analysis.
    MIT
  • Download package source from registries and scan all files for embedded licenses and copyrights, providing comprehensive analysis beyond metadata.
    Apache 2.0
  • Profile a column's distribution, outliers, coverage gaps, and dirty values. Adapts to numeric, date, text, or boolean types to reveal skew, missing days, and formatting issues.
    MIT