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⇱ Workflow builder and monitoring tools | Glama

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Workflow builder and monitoring tools

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  • Why this server?

    This server is highly relevant as it is designed to build deterministic workflows across apps and databases, handling the execution and monitoring of integration pipelines automatically.

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    A service that enables agents to build deterministic workflows across apps, databases and APIs using natural language, handling schema mapping, drift detection, and execution of integration pipelines automatically.
    Last updated
    14
    2,020

  • Why this server?

    This server specifically enables the creation, management, and monitoring of data pipelines, which directly addresses both the 'builder' and 'monitoring' aspects of the search.

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    Enables complete StreamSets Control Hub integration through conversational AI, allowing users to manage data pipelines, monitor jobs, and interactively build new pipelines with 44 tools across 9 StreamSets services. Features persistent pipeline builder sessions that let users create complete ETL workflows through natural language conversations.
    Last updated

  • Why this server?

    This server is dedicated to managing the complete product development lifecycle, including dependency tracking, workflow automation, and real-time project monitoring via dashboards.

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    Enables complete product development lifecycle management through 26 MCP tools for PRD, task, and plan management with dependency tracking, workflow automation, and real-time project dashboards. Supports multi-session usage with transaction safety and intelligent workflow analysis.
    Last updated
    3
    GPL 3.0

  • Why this server?

    This tool focuses on breaking down and executing complex, multi-step workflows combining tool usage with cognitive reasoning, providing a powerful system for defining and running automated flows.

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    A Model Context Protocol implementation that enables LLMs to execute complex, multi-step workflows combining tool usage with cognitive reasoning, providing structured, reusable paths through tasks with advanced control flow.
    Last updated
    9
    12
    28
    MIT

  • Why this server?

    This server explicitly focuses on the 'builder' aspect by enabling the programmatic creation and management of n8n workflows, a popular automation tool.

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    A Model Context Protocol (MCP) server for programmatically creating and managing n8n workflows.
    Last updated
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    18
    MIT

  • Why this server?

    This server integrates with n8n to manage not only the workflows themselves but also their executions and settings, covering both the building and monitoring of automation pipelines.

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    An MCP server enabling secure interaction with n8n workflows, executions, and settings via the Model Context Protocol, designed for integration with Large Language Models (LLMs).
    Last updated
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    106
    118
    MIT

  • Why this server?

    This server is used to create, manage, and monitor GitHub Actions workflows, offering a solution for monitoring automated CI/CD pipelines.

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    GitHub Actions Model Context Protocol Server that allows you to create, manage, monitor, and interact with workflows.
    Last updated
    10

  • Why this server?

    This tool enables the management and monitoring of GitLab pipelines through natural language commands, serving as a solution for observing CI/CD workflows.

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    Enables AI clients to manage GitLab pipelines through natural language commands. Supports triggering pipelines, checking status, listing pipelines, viewing jobs, and canceling pipelines across multiple GitLab instances.
    Last updated
    90
    ISC

  • Why this server?

    This server provides tools for DAG management and monitoring of Airflow system health, making it relevant for complex workflow orchestration and monitoring.

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    Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.
    Last updated
    68
    166
    MIT