"A server for orchestrating and managing AI task workflows" matching MCP servers:

Enables AI agents to discover Azure DevOps repositories, manage pull requests, and interact with PR comments and reviews via the Model Context Protocol.

Hosted workflow discovery, validation, execution, and lifecycle facade for Stromy, with Entra ID role-based scoping and Azure Container Apps integration.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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

Provides Vertex AI Search for Commerce product search as a tool, enabling AI agents to search product catalogs using natural language queries.

Intelligent AI routing and integration platform for seamless provider switching

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

A Model Context Protocol (MCP) server that exposes the EasyDeploy public REST API as tools for Claude, Cursor, Claude Code, and other MCP clients.

Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.

MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!

Enables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Enables AI-powered image and video analysis using Google Gemini and Vertex AI models. Supports analyzing single or multiple images, detecting objects with bounding boxes, and video content analysis through natural language prompts.

Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Exposes SAP AI Core APIs as MCP tools, enabling AI assistants to manage AI Core lifecycle and administration through natural language.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

Enables interaction with Azure AI Agent Service by automatically discovering agents and creating MCP tools for querying and managing agent workflows.