Webvizio MCP Server alternatives

1

Kanboard MCP Server

MCP server for seamless AI integration with Kanboard project management.

Kanboard MCP Server is a Go-based server implementing the Model Context Protocol (MCP) for integrating AI assistants with the Kanboard project management system. It enables users to manage projects, tasks, users, and workflows in Kanboard directly via natural language commands through compatible AI tools. With built-in support for secure authentication and high performance, it facilitates streamlined project operations between Kanboard and AI-powered clients like Cursor or Claude Desktop. The server is configurable and designed for compatibility with MCP standards.

15 4 MCP

2

Weblate MCP Server

Seamlessly connect AI assistants to Weblate for translation management via the Model Context Protocol.

Weblate MCP Server enables AI assistants and clients to directly manage Weblate translation projects through the Model Context Protocol (MCP). It integrates with the Weblate REST API, allowing natural language interaction for project and translation management. The tool offers multiple transport options including HTTP, SSE, and STDIO, and is optimized for large language model workflows. Full support for project, component, and translation operations is provided, with a focus on type safety and flexible environment configuration.

9 5 MCP

3

Taskade MCP

Tools and server for Model Context Protocol workflows and agent integration

Taskade MCP provides an official server and tools to implement and interact with the Model Context Protocol (MCP), enabling seamless connectivity between Taskade’s API and MCP-compatible clients such as Claude or Cursor. It includes utilities for generating MCP tools from any OpenAPI schema and supports the deployment of autonomous agents, workflow automation, and real-time collaboration. The platform promotes extensibility by supporting integration via API, OpenAPI, and MCP, making it easier to build and connect agentic systems.

90 20 MCP

4

TickTick MCP

MCP server for AI-powered TickTick task management integration

TickTick MCP is a Model Context Protocol (MCP) server that enables standardized integration of TickTick's task management features with AI assistants and developer applications. It allows programmatic access to create, update, retrieve, complete, or delete tasks and projects in TickTick via Python. Using this MCP server, AI systems can leverage TickTick's API to help automate and manage user's to-do lists and projects through natural language or other interfaces.

6 6 MCP

5

Azure DevOps MCP Server

Standardized AI access to Azure DevOps via Model Context Protocol.

Implements the Model Context Protocol (MCP) to enable AI assistants to securely and efficiently interact with Azure DevOps resources. Provides a standardized bridge for managing projects, work items, repositories, pull requests, and pipelines through natural language interfaces. Supports modular authentication and a feature-based architecture for scalability and integration. Facilitates seamless integration with AI tools such as Claude Desktop and Cursor AI.

306 93 MCP

6

TickTick MCP Server

Enable powerful AI-driven task management for TickTick via the Model Context Protocol.

TickTick MCP Server provides comprehensive programmatic access to TickTick task management features using the Model Context Protocol. Built on the ticktick-py library, it enables AI assistants and MCP-compatible applications to create, update, retrieve, and filter tasks with improved precision and flexibility. The server supports advanced filtering, project and tag management, subtask handling, and robust context management for seamless AI integration.

35 9 MCP

7

Vectorize MCP Server

MCP server for advanced vector retrieval and text extraction with Vectorize integration.

Vectorize MCP Server is an implementation of the Model Context Protocol (MCP) that integrates with the Vectorize platform to enable advanced vector retrieval and text extraction. It supports seamless installation and integration within development environments such as VS Code. The server is configurable through environment variables or JSON configuration files and is suitable for use in collaborative and individual workflows requiring vector-based context management for models.

97 21 MCP

8

Azure MCP Server

Connect AI agents with Azure services through Model Context Protocol.

Azure MCP Server provides a seamless interface between AI agents and Azure services by implementing the Model Context Protocol (MCP) specification. It enables integration with tools like GitHub Copilot for Azure and supports a wide range of Azure resource management tasks directly via conversational AI interfaces. Designed for extensibility and compatibility, it offers enhanced contextual capabilities for agents working with Azure environments.

1,178 351 MCP

9

AgentQL MCP Server

MCP-compliant server for structured web data extraction using AgentQL.

AgentQL MCP Server acts as a Model Context Protocol (MCP) server that leverages AgentQL's data extraction capabilities to fetch structured information from web pages. It allows integration with applications supporting MCP, such as Claude Desktop, VS Code, and Cursor, by providing an accessible interface for extracting structured data based on user-defined prompts. With configurable API key support and streamlined installation, it simplifies the process of connecting web data extraction workflows to AI tools.

120 28 MCP

10

MCP-Typescribe

An MCP server for serving TypeScript API context to language models.

MCP-Typescribe is an open-source implementation of the Model Context Protocol (MCP) focused on providing LLMs with contextual, real-time access to TypeScript API documentation. It parses TypeScript (and other) definitions using TypeDoc-generated JSON and serves this information via a queryable server that supports tools used by AI coding assistants. The solution enables AI agents to dynamically explore, search, and understand unknown APIs, accelerating onboarding and supporting agentic behaviors in code generation.

45 6 MCP

11

Offorte MCP Server

Bridge AI agents with Offorte proposal automation via the Model Context Protocol.

Offorte MCP Server enables external AI models to create and send proposals through Offorte by implementing the Model Context Protocol. It facilitates automation workflows between AI agents and Offorte's proposal engine, supporting seamless integration with chat interfaces and autonomous systems. The server provides a suite of tools for managing contacts, proposals, templates, and automation sets, streamlining the proposal creation and delivery process via standardized context handling. Designed for extensibility and real-world automation, it leverages Offorte's public API to empower intelligent business proposals.

4 4 MCP

12

mcp-miro

Model Context Protocol server for integrating MIRO Whiteboard with AI workflows.

mcp-miro is a Model Context Protocol (MCP) compliant server that connects the MIRO Whiteboard Application to AI-based systems, such as Claude Desktop. It enables board manipulation, sticky note creation, bulk operations, and more through standardized MCP interfaces. Users can authenticate via OAuth and interact with MIRO boards programmatically for collaborative whiteboarding and automation tasks. The server can be installed using Smithery or mcp-get and supports debugging with the MCP Inspector.

97 31 MCP

13

GitHub MCP Server

Connect AI tools directly to GitHub for repository, issue, and workflow management via natural language.

GitHub MCP Server enables AI tools such as agents, assistants, and chatbots to interact natively with the GitHub platform. It allows these tools to access repositories, analyze code, manage issues and pull requests, and automate workflows using the Model Context Protocol (MCP). The server supports integration with multiple hosts, including VS Code and other popular IDEs, and can operate both remotely and locally. Built for developers seeking to enhance AI-powered development workflows through seamless GitHub context access.

24,418 2,997 MCP

14

AtomGit MCP Server

AI-powered management and automation of AtomGit repositories via the Model Context Protocol.

AtomGit MCP Server implements the Model Context Protocol to enable AI-driven management and automation of AtomGit open collaboration platform repositories. It offers methods for managing repositories, issues, pull requests, branches, and labels, allowing seamless AI interaction with AtomGit. The server supports integration with platforms like Claude and VSCode, providing a standardized interface for AI to orchestrate complex collaboration workflows. Built with Node.js and easily deployable via npx or from source, it focuses on expanding collaborative capabilities using AI agents.

7 4 MCP

15

Baseline MCP Server

Brings web platform API support status to AI models via Model Context Protocol.

Baseline MCP Server serves as a Model Context Protocol (MCP) server, providing API endpoints to retrieve the baseline support status of web platform features. It fetches data from the Web Platform Dashboard API and delivers web API compatibility details, including browser support levels, baseline status, and usage data, to MCP clients or AI models. The server is configurable for various MCP clients including Claude Desktop and Visual Studio Code, and can also be deployed via Docker or Deno environments. It enables integration of up-to-date, machine-readable browser compatibility information with large language models and development tools.

36 3 MCP

16

Godot MCP

A Model Context Protocol (MCP) server implementation using Godot and Node.js.

Godot MCP implements the Model Context Protocol (MCP) as a server, leveraging the Godot game engine along with Node.js and TypeScript technologies. Designed for seamless integration and efficient context management, it aims to facilitate standardized communication between AI models and applications. This project offers a ready-to-use MCP server for developers utilizing Godot and modern JavaScript stacks.

1,071 124 MCP

17

kibitz

The coding agent for professionals with MCP integration.

kibitz is a coding agent that supports advanced AI collaboration by enabling seamless integration with Model Context Protocol (MCP) servers via WebSockets. It allows users to configure Anthropic API keys, system prompts, and custom context providers for each project, enhancing contextual understanding for coding tasks. The platform is designed for developers and professionals seeking tailored AI-driven coding workflows and provides flexible project-specific configuration.

104 14 MCP

18

Hive Intelligence MCP Server

Unified MCP server delivering advanced cryptocurrency and Web3 analytics.

Hive Intelligence MCP Server provides comprehensive cryptocurrency, DeFi, and Web3 analytics via the Model Context Protocol. It enables AI assistants to access and orchestrate over 200 specialized tools covering market data, on-chain analytics, portfolio tracking, and security analysis. The server offers both dynamic and category-specific analytics through a unified MCP interface, facilitating intelligent tool orchestration for diverse crypto data needs.

7 5 MCP

19

Make MCP Server (legacy)

Enable AI assistants to utilize Make automation workflows as callable tools.

Make MCP Server (legacy) provides a Model Context Protocol (MCP) server that connects AI assistants with Make scenarios configured for on-demand execution. It parses and exposes scenario parameters, allowing AI systems to invoke automation workflows and receive structured JSON outputs. The server supports secure integration through API keys and facilitates seamless communication between AI and Make's automation platform.

142 39 MCP

20

MCP Server for TheHive

Connect AI-powered automation tools to TheHive incident response platform via MCP.

MCP Server for TheHive enables AI models and automation clients to interact with TheHive incident response platform using the Model Context Protocol. It provides tools to retrieve and analyze security alerts, manage cases, and automate incident response operations. The server facilitates seamless integration by exposing these functionalities over the standardized MCP protocol through stdio communication. It offers both pre-compiled binaries and a source build option with flexible configuration for connecting to TheHive instances.

11 3 MCP

21

Inspektor Gadget MCP Server

AI-powered Kubernetes troubleshooting via Model Context Protocol.

Inspektor Gadget MCP Server provides an AI-powered debugging and inspection interface for Kubernetes clusters. Leveraging the Model Context Protocol, it enables intelligent output summarization, one-click deployment of Inspektor Gadget, and automated discovery of debugging tools from Artifact Hub. The server integrates seamlessly with VS Code for interactive AI commands, simplifying Kubernetes troubleshooting and monitoring workflows.

16 1 MCP

22

GXtract MCP Server

MCP server for seamless GroundX platform integration with modern editors.

GXtract MCP Server implements the Model Context Protocol (MCP) to facilitate direct integration between the GroundX document understanding platform and editors such as VS Code. It offers tools for document search, querying, and semantic object explanations, leveraging Python 3.12+ and FastMCP v2 for high performance. The system includes an in-memory cache to boost efficiency and reduce API calls, with support for both stdio and HTTP transport layers for maximum flexibility.

1 3 MCP

23

Lucidity MCP

Intelligent prompt-based code quality analysis for AI coding assistants.

Lucidity MCP is a Model Context Protocol (MCP) server that empowers AI coding assistants to deliver high-quality code through intelligent, prompt-driven analysis. It offers comprehensive detection of code issues across multiple quality dimensions, providing structured and actionable feedback. With language-agnostic capabilities, extensible framework, and flexible transport options, Lucidity MCP seamlessly integrates into developer workflows and AI systems.

72 20 MCP

24

MCP Linear

MCP server for AI-driven control of Linear project management.

MCP Linear is a Model Context Protocol (MCP) server implementation that enables AI assistants to interact with the Linear project management platform. It provides a bridge between AI systems and the Linear GraphQL API, allowing the retrieval and management of issues, projects, teams, and more. With MCP Linear, users can create, update, assign, and comment on Linear issues, as well as manage project and team structures directly through AI interfaces. The tool supports seamless integration via Smithery and can be configured for various AI clients like Cursor and Claude Desktop.

117 23 MCP

25

Last9 MCP Server

Enables AI agents to access real-time production observability data for automated code fixes.

Last9 MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide seamless integration between AI agents and production observability data. It allows tools and agents to fetch live logs, metrics, traces, events, and alerts from Last9 systems, supporting a range of development environments and IDEs. This enables faster debugging, automated code fixes, and insightful context directly within local development workflows.

46 8 MCP

26

Label Studio MCP Server

Bridge between Model Context Protocol clients and Label Studio for project, task, and prediction management.

Label Studio MCP Server implements a Model Context Protocol (MCP) interface to enable programmatic management of Label Studio projects, tasks, and model predictions. It enables structured interactions with a running Label Studio instance via MCP clients, supports various project and task operations, and integrates the official Label Studio SDK. The tool exposes multiple functions for project management, task handling, and prediction integration, allowing both natural language and structured API calls.

23 8 MCP

27

MCP Miro Server

Miro board integration for AI assistants via Model Context Protocol.

MCP Miro Server provides a standardized MCP server interface to the Miro platform, enabling AI assistants to access and manage Miro boards programmatically. It supports a wide range of board and item operations, including creating, listing, updating, and deleting boards and their contents. Secure OAuth token access ensures integration with users’ Miro accounts. Designed to work seamlessly with AI tools like Claude Desktop, it allows efficient and automated Miro workspace management.

57 16 MCP

28

Agentset MCP

Open-source MCP server for Retrieval-Augmented Generation (RAG) document applications.

Agentset MCP provides a Model Context Protocol (MCP) server designed to power context-aware, document-based applications using Retrieval-Augmented Generation. It enables developers to rapidly integrate intelligent context retrieval into their workflows and supports integration with AI platforms such as Claude. The server is easily installable via major JavaScript package managers and supports environment configuration for namespaces, tenant IDs, and tool descriptions.

22 10 MCP

29

Plugwise MCP Server

TypeScript-based Model Context Protocol server for Plugwise smart home integration.

Plugwise MCP Server is a TypeScript-based server that implements the Model Context Protocol (MCP) for integrating Plugwise smart home devices. It enables automatic discovery and secure management of Plugwise hubs, provides control over thermostats, switches, and smart plugs, and supports real-time device updates and energy monitoring. Designed for compatibility with popular MCP clients such as Claude Desktop, Cline, Cursor, and VS Code Copilot via standard I/O transport, it offers robust support for multiple hubs and both mock and real hardware environments.

0 1 MCP

30

Mastra

A TypeScript framework for building scalable AI-powered agents and applications.

Mastra is a modern TypeScript-based framework designed for developing AI-powered applications and autonomous agents. It offers model routing to integrate over 40 AI providers, a graph-based workflow engine, advanced context management, and production-ready tools for observability and evaluation. Mastra features built-in support for authoring Model Context Protocol (MCP) servers, enabling standardized exposure of agents, tools, and structured AI resources via the MCP interface.

18,189 1,276 MCP

31

VictoriaMetrics MCP Server

Model Context Protocol server enabling advanced monitoring and observability for VictoriaMetrics.

VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

87 11 MCP

32

Slite MCP Server

Bridge Slite notes with AI model context using the MCP standard.

Slite MCP Server implements the Model Context Protocol to interface with Slite's API, enabling seamless search, retrieval, and hierarchical browsing of workspace notes. It exposes standardized tools for searching notes, retrieving content by ID, and navigating note structures, making Slite content programmatically accessible to contextual AI pipelines. Built in Node.js and TypeScript, it is configurable and supports authentication via API key.

0 0 MCP

33

Jira MCP

AI-Ready Jira Server for Real-World Developer Workflows

Jira MCP is an opinionated server implementation of the Model Context Protocol (MCP) tailored for Jira automation and integration. It provides advanced tools to manage Jira issues, sprints, development data, and project versions, reflecting workflows of real engineering and QA teams. Designed for seamless AI and tool integrations, it supports context-rich retrieval of Jira information for enhancing development transparency and automation.

69 19 MCP

34

Web Analyzer MCP

Intelligent web content analysis and summarization via MCP.

Web Analyzer MCP is an MCP-compliant server designed for intelligent web content analysis and summarization. It leverages FastMCP to perform advanced web scraping, content extraction, and AI-powered question-answering using OpenAI models. The tool integrates with various developer IDEs, offering structured markdown output, essential content extraction, and smart Q&A functionality. Its features streamline content analysis workflows and support flexible model selection.

2 3 MCP

35

Maven Tools MCP Server

Universal Maven Central dependency intelligence server for JVM build tools via the Model Context Protocol.

Maven Tools MCP Server provides an MCP-compliant API delivering rich Maven Central dependency intelligence for JVM build tools like Maven, Gradle, SBT, and Mill. It enables AI assistants to instantly analyze, interpret, and recommend updates, health checks, and maintenance insights by reading maven-metadata.xml directly from Maven Central. With Context7 integration, it supports orchestration and documentation, enabling bulk analysis, stable version filtering, risk assessment, and rapid cached responses. Designed for seamless integration into AI workflows via the Model Context Protocol.

14 2 MCP

36

GitLab MR MCP

An MCP server for AI-powered interaction with GitLab merge requests and issues.

GitLab MR MCP implements a server for the Model Context Protocol (MCP) enabling AI agents to perform structured interactions with GitLab repositories. It provides capabilities for reading merge request and issue details, listing projects, fetching diffs and comments, and making changes such as commenting or updating titles and descriptions. Installation is supported via Smithery or manually, and integration with MCP clients and Inspector tools is documented for development and troubleshooting.

65 19 MCP

37

@growi/mcp-server

Bridge GROWI wiki content to AI models with context-aware access and management.

@growi/mcp-server acts as a Model Context Protocol (MCP) server that enables AI models to access, search, and manage GROWI wiki content within an organization. It facilitates seamless connection between multiple GROWI instances and language models, enhancing information retrieval and knowledge management capabilities. The platform provides comprehensive tools for page, tag, comment, and revision management as well as share link and user activity tracking. Its flexible configuration allows simultaneous operation with several GROWI apps for scalable deployment.

10 7 MCP

38

WebScraping.AI MCP Server

MCP server for advanced web scraping and AI-driven data extraction

WebScraping.AI MCP Server implements the Model Context Protocol to provide web data extraction and question answering functionalities. It integrates with WebScraping.AI to offer robust tools for retrieving, rendering, and parsing web content, including structured data and natural language answers from web pages. It supports JavaScript rendering, proxy management, device emulation, and custom extraction configurations, making it suitable for both individual and team deployments in AI-assisted workflows.

33 13 MCP

39

Authenticator App MCP Server

Secure MCP server for AI-assisted access to 2FA codes and passwords.

Authenticator App MCP Server provides a secure Model Context Protocol (MCP) server enabling AI agents to interact with authentication credentials, such as 2FA codes and passwords. It facilitates automated login processes for AI assistants while maintaining robust security by requiring access tokens and integrating with the Authenticator App desktop client. This solution streamlines the management of user credentials across multiple platforms and websites, ensuring seamless and secure credential retrieval by AI agents.

27 10 MCP

40

MCP Router

A Unified MCP Server Management App

MCP Router is a cross-platform desktop application designed to simplify the management of Model Context Protocol (MCP) servers. It enables users to centrally manage, organize, and monitor multiple MCP servers, both locally and remotely, with support for various connection methods. The app offers advanced context organization through Projects and Workspaces, as well as tools toggling and comprehensive logging. With a focus on privacy, all data is stored locally, and integration capabilities allow seamless connection with popular AI tools.

1,078 95 MCP

41

ws-mcp

WebSocket bridge for MCP stdio servers.

ws-mcp wraps Model Context Protocol (MCP) stdio servers with a WebSocket interface, enabling seamless integration with web-based clients and tools. It allows users to configure and launch multiple MCP servers via a flexible configuration file or command-line arguments. The tool is designed to be compatible with services such as wcgw, fetch, and other MCP-compliant servers, providing standardized access to system operations, HTTP requests, and more. Integration with tools like Kibitz enables broader applications in model interaction workflows.

19 7 MCP

42

Scrapeless MCP Server

A real-time web integration layer for LLMs and AI agents built on the open MCP standard.

Scrapeless MCP Server is a powerful integration layer enabling large language models, AI agents, and applications to interact with the web in real time. Built on the open Model Context Protocol, it facilitates seamless connections between models like ChatGPT, Claude, and tools such as Cursor to external web capabilities, including Google services, browser automation, and advanced data extraction. The system supports multiple transport modes and is designed to provide dynamic, real-world context to AI workflows. Robust scraping, dynamic content handling, and flexible export formats are core parts of the feature set.

57 10 MCP

43

Web3 Jobs MCP Server

AI-ready MCP server delivering curated, real-time Web3 job listings.

Web3 Jobs MCP Server provides real-time access to curated Web3 job listings from web3.career through a Model Context Protocol (MCP) interface, enabling intelligent job discovery for AI agents. The server supports advanced filtering by location, remote status, job tag, and result limits, and returns results in Markdown format. It enables the generation of natural language prompts for job searches, facilitating seamless integration with AI platforms such as Claude Desktop. Designed for Python 3.10+, it offers flexible deployment and configuration options.

4 3 MCP

44

Context Apps MCP

AI-powered productivity suite unified by the Model Context Protocol.

Context Apps MCP is an AI-powered productivity suite that connects Todo, Idea, Journal, and Timer applications through the Model Context Protocol, enabling smart, context-driven workflows with apps like Claude Desktop and other MCP-compatible clients. It allows users to manage tasks, develop ideas, analyze journals, and optimize productivity using AI, all accessible and integrated via MCP-compliant endpoints. The suite ensures secure authentication via Apple ID OAuth, provides end-to-end encrypted communication, and offers users complete control over their data.

5 2 MCP

45

Coda MCP Server

A Model Context Protocol server enabling seamless interaction with Coda documents and pages.

Coda MCP Server implements a Model Context Protocol (MCP) server that bridges AI assistants or MCP clients with the Coda API. It provides standardized tools for listing, creating, reading, updating, duplicating, and renaming Coda pages, as well as handling document context. The server communicates over standard input/output, supporting integration with platforms like Cursor and Claude Desktop, and can be deployed via Node.js or Docker.

36 22 MCP

46

Binary Ninja MCP

Seamlessly integrate Binary Ninja with Model Context Protocol clients for enhanced reverse engineering.

Binary Ninja MCP enables real-time integration of Binary Ninja's reverse engineering environment with various Model Context Protocol (MCP) clients. It acts as a server exposing Binary Ninja's capabilities via HTTP endpoints and includes a bridge to connect to MCP clients. The extension supports auto-setup with popular clients such as Cline, Claude Desktop, Roo Code, and others, streamlining the use of AI-assisted workflows. This enhances tasks such as analyzing binaries, switching targets, and leveraging LLM-driven automation in reverse engineering.

112 35 MCP

47

FastMCP

TypeScript framework for building robust MCP servers with minimal setup.

FastMCP is a TypeScript framework designed for building servers that adhere to the Model Context Protocol (MCP), enabling efficient management of client sessions and context. It streamlines the creation of MCP servers by providing intuitive APIs, built-in authentication, session and request tracking, and support for handling various content types such as images and audio. The framework also enforces best practices around error handling, logging, and streaming outputs. Developers benefit from reduced boilerplate and a focus on core MCP functionality.

2,738 231 MCP

48

sentry-mcp

Remote MCP middleware for developer workflow and debugging tools.

sentry-mcp provides a remote Model Context Protocol server designed as middleware for Sentry's API, specifically optimized for human-in-the-loop coding agents and developer-oriented workflows. It enables integration with coding assistants like Cursor and Claude Code, offering both remote and stdio transports for varied environments, including self-hosted instances. The project also supports AI-powered search tools for querying events and issues, leveraging OpenAI API for natural language processing. Additionally, an Inspector tool is included for service testing and integration validation.

424 51 MCP

49

Jira Communication Server MCP Server

A TypeScript-based MCP server for seamless Jira interactions

Jira Communication Server MCP Server enables integration with Jira by exposing standardized tools for querying, creating, editing, and managing Jira issues via the Model Context Protocol. It supports a wide range of Jira operations, including executing JQL queries, managing tickets, handling attachments, assigning tickets, and interacting with Jira projects and statuses. The server is designed for use in environments supporting the MCP, such as Claude Desktop, and provides debugging utilities for MCP communication.

25 7 MCP

50

mcp-server-apache-airflow

A Model Context Protocol server for integrating Apache Airflow with MCP clients.

mcp-server-apache-airflow provides a Model Context Protocol (MCP) server implementation that allows standardized interaction with Apache Airflow environments. By wrapping Airflow's REST API, it enables MCP clients to manage and orchestrate workflows, DAGs, and runs in a consistent and interoperable manner. This implementation leverages the official Apache Airflow client library to ensure robust compatibility and maintainability. It streamlines the management of Airflow resources by exposing comprehensive endpoint coverage for key workflow operations.

109 28 MCP

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