"Apache Solr" matching MCP servers:

Provides managed Apache Solr search as MCP tools, enabling hybrid retrieval, server-side GPU embeddings, document indexing, and grounded RAG answers without managing infrastructure.

Backend service implementing the Model Control Panel protocol that connects to Apache Doris databases, allowing users to execute SQL queries, manage metadata, and potentially leverage LLMs for tasks like natural language to SQL conversion.

MCP Server for Apache Pinot

This read-only MCP Server allows you to connect to Apache Cassandra 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/).

A FastMCP integration server that provides access to Apache Gravitino metadata management APIs, allowing users to manage catalog/schema/table metadata, tags, and user-role information through a structured interface.

This read-only MCP Server allows you to connect to Apache Hadoop Hive 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/).

Enables MCP-capable agents to inspect, validate, search, and manage Apache Hop pipelines and workflows, with guarded editing, backup, and optional local or Hop Server execution.

Manage Apache Kafka on Kubernetes via Strimzi. Clusters, topics, users, connectors, MirrorMaker2, and node pools.

An MCP server that wraps the Apache Airflow REST API, enabling clients to manage DAGs, monitor task instances, and handle workflows through a standardized interface. It provides comprehensive access to Airflow features including DAG runs, variables, connections, and XComs.

MCP server that lets AI assistants and LLMs interact with Apache Flink clusters through natural language: cluster/job monitoring, metrics, exception tracking, TaskManager resources, and multi-cluster support via the Flink REST API.

This read-only MCP Server allows you to connect to Apache Hbase data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for Apache Hbase (https://www.cdata.com/drivers/hbase/download/mcp).

Enables AI-controlled management of Apache Beam data pipelines across different runners (Flink, Spark, Dataflow, Direct) via the Model Context Protocol.

Provides integration with Apache Airflow's REST API, allowing AI assistants to programmatically interact with Airflow workflows, monitor DAG runs, and manage tasks.

MCP server for lossless YAML 1.2 editing by AI agents. Two tools — noyalib_get (read a value at a dotted/indexed path) and noyalib_set (write a value, preserving comments/formatting byte-for-byte). Pure Rust, streaming-first serde, JSON Schema validation. MIT OR Apache-2.0.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

An MCP server that converts Apache Airflow DAGs into Prefect flows. It provides tools to read DAGs, lookup translation knowledge, validate code, search Prefect docs, scaffold projects, deploy, and generate migration reports.

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.

MCP server exposing Apache Airflow REST API operations as tools — list DAGs, inspect runs and task instances, trigger DAG runs, and check failed DAGs and scheduler health

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.