"Apache Spark" matching MCP servers:

Enables interaction with Apache Airflow through the Model Context Protocol, allowing users to manage DAGs, task instances, variables, connections, pools, XComs, and datasets.

Enables AI agents to manage and interact with Apache NiFi through its REST API, covering process groups, processors, connections, queues, provenance, and version control via natural language tool calls.

Enables sending and receiving Telegram messages through MCP clients like Claude Desktop and Gemini Spark.

Enables natural language interaction with Apache Airflow for querying DAGs, monitoring execution, and troubleshooting failures.

Enables AI agents to interact with Apache Kafka through natural language, supporting operations like producing/consuming messages, managing topics, and querying brokers, partitions, and consumer group offsets.

Enables AI models to publish and consume messages from Apache Kafka topics through a standardized interface, making it easy to integrate Kafka messaging with LLM and agent applications.

Enables interaction with Apache Kafka topics, allowing users to publish messages to and read messages from Kafka instances through natural language.

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

Streamable HTTP bridge that exposes OfficeCLI MCP tools (create, view, query, etc.) to Gemini Spark via a hosted server, deployable on Coolify.

Connects MCP clients like Claude, Codex, and Cursor to a running Autodesk Revit session for typed BIM queries, verified model edits, family authoring, exports, and Power BI workflows. It is open-source, Apache-2.0, and designed for reliable, verified outcomes.

A stateless MCP server that wraps OfficeCLI to create and edit Microsoft Word documents via AI instructions, outputting Base64 Data URLs for serverless environments like Vercel.

Enables Claude to inspect and operate Apache Airflow over its REST API, providing read tools and safe write operations (gated by read-only mode) for managing DAGs, runs, tasks, and pools.

Enables management of Amazon Managed Workflows for Apache Airflow (MWAA) environments and operations including DAG management, workflow execution monitoring, and access to Airflow connections and variables through a unified interface.

Enables autonomous task execution and direct desktop computer control through ByteBot's dual-API architecture, supporting intelligent hybrid workflows with mouse/keyboard operations, screen capture, file I/O, and automatic intervention handling.

Enables autonomous multi-turn negotiation and counter-offer strategy by calculating ZOPA, concession decay curves, reservation price thresholds, and structured bargaining offers.

Enables turning natural-language vacation or business travel goals into multi-leg flight segments, lodging choices, layover buffers, baggage fee optimization, and consolidated reservation manifests via MCP.

An MCP server that authenticates incoming webhooks from multiple providers such as Shopify, Stripe, GitHub, Slack, and PayPal using HMAC-SHA256 constant-time verification and timestamp replay-window validation. It lets agents validate and multiplex verified webhook events into dispatched event streams.

Enables forecasting SKU demand with exponential moving averages, computing safety-stock buffers and reorder points, and generating supplier purchase orders through an MCP JSON-RPC 2.0 interface.

Enables agents to perform real-time multi-merchant price comparison, coupon stacking, delivery-speed trade-off analysis, stock volatility tracking, and optimal purchase routing across commerce platforms. It exposes these capabilities as an MCP-compatible tool for automated inventory and arbitrage decisions.

Enables ingesting FedEx, UPS, DHL, and SF Express carrier tracking webhooks to detect failed delivery attempts and customs delays, then compute and dispatch recovery options. Supports autonomous negotiation of delivery windows, parcel locker holds, and neighbor safe-drop instructions through MCP JSON-RPC 2.0 tools.