jaimeferj/mcp-iceberg
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Apache Iceberg MCP Server is a comprehensive Model Context Protocol server designed to enable LLMs like Claude to efficiently interact with Iceberg data lakes.
Tools
Functions exposed to the LLM to take actions
list_tables
List all tables in namespaces
get_schema
Get detailed schema information with types and metadata
get_partitioning
View partition specifications and transforms
get_table_properties
Access table configuration and properties
get_snapshots
List available snapshots for time travel
get_table_stats
Get basic statistics (row count, file count, size)
sample_data
Get sample rows with optional random sampling
get_null_counts
Count null values per column with percentages
get_distinct_counts
Count distinct values per column
get_value_distribution
Get top N most frequent values with counts
check_duplicates
Detect duplicate rows based on specified columns
get_column_stats
Statistical summary for numeric columns (min, max, avg, std)
preview_partitions
Show existing partitions and their sizes
search_values
Search for rows containing specific values
get_data_types_summary
Get data type distribution
validate_schema_evolution
Show schema evolution history
get_file_stats
Get information about data files
analyze_skew
Detect partition imbalance
get_table_metadata
Get complete metadata for optimization
execute_query
Execute queries using pandas query syntax
get_column_names
Get simple list of column names
check_table_exists
Verify if a table exists
get_latest_snapshot
Get most recent snapshot details
filter_preview
Preview data with filters applied
Prompts
Interactive templates invoked by user choice
No prompts
Resources
Contextual data attached and managed by the client