PySpark MCP

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Tools (14)

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• analytics

  **Deprecated.** Prefer ``review``. Still registered this minor version. Analytics on optimization effectiveness and usage patterns. **Modes:** ``optimization`` Get analytics on optimization effectiveness. *Parameters:* ``optimization_type``, ``limit`` ``usage`` Get usage statistics including conversion history and pattern stats. *Parameters:* ``limit``

• analyze

  **Deprecated.** Prefer ``convert`` / ``glue_job`` / ``review``. Still registered this minor version. Analyze SQL or PySpark code for context, data flow, or optimization opportunities. **Modes:** ``sql_context`` Analyze SQL context (schemas, tables, dialect, complexity). *Parameters:* ``sql_content`` or ``selected_text`` ``data_flow`` Analyze data flow patterns in PySpark code. *Parameters:* ``pyspark_code`` (required), ``table_info`` ``codebase`` Analyze a PySpark codebase directory for patterns and issues. *Parameters:* ``directory_path`` (required), ``include_opt…

• batch_status

  **Deprecated.** Prefer ``convert(mode="batch_dir")``. Still registered this minor version. Monitor and manage batch processing jobs. **Modes:** ``status`` Get the status of a specific batch job. *Parameters:* ``job_id`` (required) ``cancel`` Cancel a running batch job. *Parameters:* ``job_id`` (required) ``active`` List all currently active batch jobs. *Parameters:* none ``recent`` List recent batch jobs. *Parameters:* ``limit``, ``status``

• context

  **Deprecated.** Prefer ``convert``. Still registered this minor version. Store, retrieve, and work with SQL/PySpark conversion context. **Modes:** ``store`` Store additional context data for a conversion. *Parameters:* ``conversion_id`` (required), ``context_data`` (required) ``get`` Retrieve stored context for a conversion. *Parameters:* ``conversion_id`` (required) ``assist`` Real-time SQL assistance — analyze and convert as you edit. *Parameters:* ``sql_query`` or ``selected_text``

• convert

  Convert SQL to PySpark code or process SQL files in batch. **Modes:** ``sql`` Convert a single SQL query to PySpark code. *Parameters:* ``sql_query`` (required), ``table_info``, ``dialect``, ``optimization_level``, ``include_glue_template``, ``style`` (``production`` | ``notebook``), ``target`` (``spark`` | ``glue``) ``batch_files`` Process multiple SQL files into PySpark. *Parameters:* ``file_paths`` (required list), ``output_dir``, ``job_name`` ``batch_dir`` Process all SQL files in a directory. *Parameters:* ``directory_path`` (required), ``output_dir``, …

• glue_data

  **Deprecated.** Prefer ``glue_job``. Still registered this minor version. Generate AWS Glue data processing jobs — incremental, CDC, bookmarks. **Modes:** ``incremental`` Generate Glue job with incremental processing and job bookmarking. *Parameters:* ``source_database`` (required), ``source_table`` (required), ``target_database`` (required), ``target_table`` (required), ``incremental_column`` (required), ``incremental_strategy``, ``transformation_sql`` ``cdc`` Generate Change Data Capture (CDC) Glue job. *Parameters:* ``source_database`` (required), ``source_ta…

• glue_job

  Generate and manage AWS Glue job configurations and templates. **Modes:** ``template`` Generate a complete AWS Glue job template. *Parameters:* ``sql_query``, ``job_name``, ``source_database``, ``source_table``, ``target_database``, ``target_table``, ``output_dir``, ``source_format``, ``target_format``, ``include_bookmarking``, ``template_type``, ``script_name`` ``dynamic_frame`` Convert PySpark DataFrame code to use DynamicFrames. *Parameters:* ``pyspark_code`` (required), ``source_database``, ``source_table``, ``target_database``, ``target_table`` ``properties…

• glue_s3

  **Deprecated.** Prefer ``glue_job``. Still registered this minor version. Analyze S3 data layouts using **path heuristics** (no AWS API call). **Modes:** ``analyze`` Path-heuristic layout suggestions. No AWS call; figures are not measured. *Parameters:* ``s3_location`` (required), ``database_name`` (required), ``table_name`` (required), ``data_format``, ``query_patterns``, ``data_size_gb`` ``optimize`` Generate comprehensive S3 optimization strategy. *Parameters:* ``database_name`` (required), ``table_name`` (required), ``s3_location`` (required), ``data_format``, `…

• glue_schema

  **Deprecated.** Prefer ``glue_job``. Still registered this minor version. Manage Glue Data Catalog schemas — detect, evolve, and define. **Modes:** ``detect`` Detect schema from sample data and generate table definition. *Parameters:* ``sample_data`` (required dict/list), ``table_name`` (required), ``infer_partitions`` ``evolve`` Generate schema evolution strategy for handling schema changes. *Parameters:* ``current_columns`` (required), ``new_columns`` (required), ``merge_behavior``, ``case_sensitive`` ``catalog`` Generate AWS Glue Data Catalog table definitio…

• optimize

  **Deprecated.** Prefer ``review``. Still registered this minor version. Optimize PySpark code and recommend performance improvements. **Modes:** ``code`` Return pattern-based suggestions for PySpark code. Does **not** rewrite the input. *Parameters:* ``code`` (required), ``optimization_level`` ``joins`` Recommend join strategies based on estimated table sizes. *Parameters:* ``pyspark_code`` (required), ``table_info`` ``partitioning`` Suggest optimal partitioning strategies. *Parameters:* ``pyspark_code`` (required), ``table_info`` ``comprehensive`` Generate co…

• refactor

  **Deprecated.** Prefer ``review``. Still registered this minor version. Refactor PySpark code and generate pipeline structures. **Modes:** ``patterns`` Refactor code by replacing duplicate patterns with utility function calls. *Parameters:* ``original_code`` (required), ``code_samples`` (required) ``utilities`` Extract common utility functions from code patterns. *Parameters:* ``code_samples`` (required), ``patterns`` ``pipeline`` Generate optimized PySpark data pipeline code or project structure. *Parameters (pipeline):* ``data_sources`` (required list), ``process…

• review

  Review PySpark code for issues, patterns, and refactoring opportunities. **Modes:** ``code`` Review PySpark code for issues, best practices, and performance. *Parameters:* ``code`` (required), ``focus_areas`` ``patterns`` Analyze code samples to discover common patterns. *Parameters:* ``code_samples`` (required list) ``duplicates`` Detect duplicate patterns across code samples. *Parameters:* ``code_samples`` (required list)

• s3_source

  **Deprecated.** Prefer ``glue_job``. Still registered this minor version. Analyze S3 data sources and Delta tables. **Modes:** ``analyze`` Analyze S3 data source structure, format, and optimization opportunities. *Parameters:* ``s3_path`` (required), ``include_schema_inference`` ``delta`` Analyze Delta table structure, properties, and optimization. *Parameters:* ``table_path`` (required), ``analyze_history``

• search

  **Deprecated.** Prefer ``convert``. Still registered this minor version. Search stored conversions, code patterns, and context data. **Modes:** ``conversions`` Search previously converted SQL queries and history. *Parameters:* ``query``, ``limit`` If ``query`` is empty, returns recent conversion history. ``patterns`` Search stored code patterns by description or template. *Parameters:* ``query``, ``limit``, ``min_usage_count`` If ``query`` is empty, returns all stored patterns with ``min_usage_count``. ``context`` Retrieve stored conversion context. *Parame…

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Last commit

Oct 18, 2026 (11 days ago)

Last release

Oct 18, 2026 (11 days ago)

Last package publish

Aug 29, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name

io.github.AnnasMazhar/pyspark-mcp

Version

0.1.0

Auth

No auth

Packages

pypi pyspark-tools

License

MIT

Repository

github.com/AnnasMazhar/pyspark_mcp

First seen

Oct 24, 2026

Last checked

Oct 25, 2026

Source

Official MCP Registrygithub-graphql