"Campaign Monitor" matching MCP servers:

🤖 Enable AI assistants (Claude, Cursor) to monitor, diagnose, and query Amazon Redshift using this MCP server and the AWS Data API.

A config-driven MCP server that exposes OData and REST APIs as MCP tools, enabling AI assistants to query, manage, and monitor SAP backends through natural language.

Provides worktree-aware semantic code indexing and search via MCP, enabling agents to query indexed code and monitor indexing status while keeping lifecycle operations separate.

Enables local-first, source-cited AI answers about your TTRPG campaign lore from your own documents, usable in Discord, Foundry VTT, or any MCP client while refusing to invent information outside your sources.

A tool that connects Google Ads with Claude AI, allowing users to analyze advertising data through natural language conversations and access campaign information, performance metrics, keyword analytics, and ad management.

Enables SafeOps operators to monitor worker health, inspect job queues, investigate incidents, search runbooks, and approve or reject targeted failed-job retries through MCP tools, resources, and a prompt.

Enables AI agents to monitor web documentation for changes, perform semantic search with RAG, and analyze breaking changes in APIs.

Enables AI agents to convert files, render web pages to markdown/PDF/screenshots, search the live web, extract structured data, ingest RAG-ready chunks, and monitor pages for changes through a single API key.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

Enables AI assistants to monitor and analyze public opinion, trends, and news from multiple platforms, with support for RSS, keyword filtering, AI translation, sentiment analysis, and trend predictions via natural language conversation.

Enables AI assistants to interact with CrowdCent's prediction challenges, allowing them to access challenges, download datasets, submit predictions, and monitor submissions through natural language commands.

Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2

MCP server for creating and managing Mindola lenses, which are grounded AI pages that answer questions from your own material with citations. Enables AI assistants to create lenses, add knowledge, and monitor status through natural language.

Enables MCP-compatible clients to search and query a team knowledge graph, retrieve document context, upload files for indexing, explore entities and connections, and monitor workspace usage and server health.

Enables agentic systems to search and retrieve conference talk details, ask grounded questions about the conference, list talks and concepts, and monitor server queue status via native MCP tools.