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Average Ratings 0 Ratings
Description
The Microsoft MCP Gateway serves as an open-source reverse proxy and management interface for Model Context Protocol (MCP) servers, facilitating scalable and session-aware routing along with lifecycle management and centralized oversight of MCP services, particularly within Kubernetes setups. Acting as a control plane, it adeptly directs requests from AI agents (MCP clients) to the corresponding backend MCP servers while maintaining session affinity, effectively managing multiple tools and endpoints through a singular gateway that prioritizes authorization and observability. Additionally, it empowers teams to deploy, update, and remove MCP servers and tools through RESTful APIs, enabling the registration of tool definitions and the management of these resources with security measures such as bearer tokens and role-based access control (RBAC). The architecture distinctly separates the management of the control plane, which includes CRUD operations on adapters, tools, and metadata, from the data plane's routing capabilities, which support streamable HTTP connections and dynamic tool routing, thus providing advanced features like session-aware stateful routing. This design not only enhances operational efficiency but also fosters a more secure environment for managing AI services.
Description
dstack simplifies GPU infrastructure management for machine learning teams by offering a single orchestration layer across multiple environments. Its declarative, container-native interface allows teams to manage clusters, development environments, and distributed tasks without deep DevOps expertise. The platform integrates natively with leading GPU cloud providers to provision and manage VM clusters while also supporting on-prem clusters through Kubernetes or SSH fleets. Developers can connect their desktop IDEs to powerful GPUs, enabling faster experimentation, debugging, and iteration. dstack ensures that scaling from single-instance workloads to multi-node distributed training is seamless, with efficient scheduling to maximize GPU utilization. For deployment, it supports secure, auto-scaling endpoints using custom code and Docker images, making model serving simple and flexible. Customers like Electronic Arts, Mobius Labs, and Argilla praise dstack for accelerating research while lowering costs and reducing infrastructure overhead. Whether for rapid prototyping or production workloads, dstack provides a unified, cost-efficient solution for AI development and deployment.
API Access
Has API
API Access
Has API
Integrations
Microsoft Azure
Amazon Web Services (AWS)
Docker
Google Cloud Platform
Kubernetes
Microsoft Entra ID
Model Context Protocol (MCP)
Python
Visual Studio Code
Integrations
Microsoft Azure
Amazon Web Services (AWS)
Docker
Google Cloud Platform
Kubernetes
Microsoft Entra ID
Model Context Protocol (MCP)
Python
Visual Studio Code
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
microsoft.github.io/mcp-gateway/
Vendor Details
Company Name
dstack
Founded
2022
Country
Germany
Website
dstack.ai/