Apache Spark is an open-source unified analytics engine for large-scale data processing. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs.
Provides tools for searching and retrieving Apache Spark documentation, enabling full-text keyword searches with section filtering and access to the full content of documentation pages.
Provides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.
2
MIT
Why this server?
Provides read-only access to Apache Spark data through SQL models, allowing for querying live data via natural language questions without requiring SQL knowledge. Tools include listing available tables, retrieving column information, and executing SQL SELECT queries against Spark.
This read-only MCP Server allows you to connect to Apache Spark data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).
MIT
Why this server?
Offers information about Duyet's expertise with Apache Spark through CV resources and tools, enabling discussions about data engineering projects.
An experimental Model Context Protocol server that enables AI assistants to access information about Duyet, including his CV, blog posts, and GitHub activity through natural language queries.
8
2
Why this server?
Provides tools for diagnosing Spark job failures and optimizing Spark performance, using error logs and source code to identify root causes and suggest fixes.
MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.
1
MIT
Why this server?
Provides searchable documentation for Apache Spark as part of the data engineering knowledge base.
Provides AI assistants with searchable access to documentation from 170+ curated repositories and 1000+ popular GitHub projects across 20+ categories including trading, AI/ML, DevOps, and web development.
3
MIT
Why this server?
Query Spark SQL clusters via Thrift/HiveServer2 protocol, enabling read-only SQL queries, schema discovery, and multiple authentication methods.
MCP server with 32 tools for ETL ingestion, AI-generated data quality rules, AI
transformations, vector search, and natural-language SQL. Works across Postgres,
MongoDB, Kafka, S3/MinIO, HashiCorp Vault, and five vector stores
(Qdrant, Weaviate, Milvus, Chroma, pgvector).
12
AGPL 3.0
Why this server?
Supports Apache Spark SQL dialect for SQL generation, schema introspection, validation, and transpilation.
An MCP server that provides SQL generation, validation, transpilation, and schema introspection across 10 SQL dialects, using a property graph schema and phase-locked reasoning to convert natural language to accurate SQL.
2
MIT
Why this server?
Provides query optimization and data discovery capabilities for Apache Spark by exposing logical and physical query plans, catalog and table information to AI systems.
A server implementation of MCP for Apache Spark that provides query plans and catalog information to AI systems for query optimization and data discovery.
