"Campaign Monitor" matching MCP servers:

An MCP server that orchestrates deterministic analytics, benchmarks, recommendations, and forecasting to provide AI-driven campaign analysis and executive reports.

An MCP server for controlling Fivetran data pipelines. Enables AI assistants to manage syncs, monitor connection status, and control pipelines through natural language.

Enables MCP-capable clients to monitor and manage Apache Kafka clusters, including topics, partitions, configs, and consumer groups with lag, while enforcing configurable security modes, topic allowlists, protected topics, and audit logging.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

This MCP server enables interaction with the Polytomic API to manage data connections, models, and synchronization tasks. It supports both Reverse ETL and ELT operations, allowing users to trigger syncs, monitor execution status, and configure data pipelines.

Enables AI agents to interact with Dagster instances, explore data pipelines, monitor runs, and manage assets.

Enables users to interact with Apache Airflow through MCP to monitor DAGs, inspect runs and logs, and diagnose task failures using natural language.

An MCP server that gives Claude access to Ogury's campaign reporting API, enabling retrieval of campaign performance metrics and reports through natural language queries.

Enables AI agents to create, manage, and monitor two-way data syncs between platforms like Airtable, Webflow, HubSpot, Salesforce, Notion, and Postgres, including mapping fields, running syncs, and troubleshooting record-level issues.

Enables AI agents to operate a US power-grid data pipeline – ingest, plan, run, and monitor datasets like CAISO, ERCOT, and EIA-930 through MCP tools that mirror the CLI.

Turns natural language into data pipeline actions using six specialist agents that collaborate through MCP to build, validate, and monitor data infrastructure.

Enables AI assistants to create, monitor, and manage computational tasks through GA4GH Task Execution Service (TES) functionality. Provides seamless access to TES-compliant services for executing bioinformatics and scientific computing workflows.

An MCP server that exposes Azure Data Factory operations as tools any LLM can call — trigger pipelines, monitor runs, inspect datasets, and get factory health summaries through natural language.

Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.

An MCP server that enables interaction with Kafka clusters to manage topics, monitor consumer groups, and stream messages. It provides a comprehensive suite of tools for broker metadata inspection and local Kafka user management.

An MCP server that exposes live game data from Workers & Resources: Soviet Republic to Claude by parsing game autosave files. It enables users to monitor population demographics, economic metrics, and trade history through natural language queries.

Provides real-time US power grid intelligence and carbon intensity data to enable carbon-aware AI compute scheduling across major grid regions. It allows users to monitor energy generation and optimize workloads based on renewable energy availability and grid load forecasts.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

Provides full execution and management capabilities for Microsoft Fabric Data Engineering workloads, including notebooks, pipelines, Lakehouses, and Spark jobs. It enables users to trigger runs, monitor status, manage workspace items, and configure job schedules through natural language.

Enables natural language-powered ETL workflows using Airflow, AWS Glue, Athena, and S3, allowing LLM agents to control and monitor data infrastructure.