Best AI Gateways for Visual Studio Code

Compare the Top AI Gateways that integrate with Visual Studio Code as of April 2026

This a list of AI Gateways that integrate with Visual Studio Code. Use the filters on the left to add additional filters for products that have integrations with Visual Studio Code. View the products that work with Visual Studio Code in the table below.

What are AI Gateways for Visual Studio Code?

AI gateways, also known as LLM gateways, are advanced systems that facilitate the integration and communication between artificial intelligence models and external applications, networks, or devices. They act as a bridge, enabling AI systems to interact with different data sources and environments, while managing and securing data flow. These gateways help streamline AI deployment by providing access control, monitoring, and optimization of AI-related services. They often include features like data preprocessing, routing, and load balancing to ensure efficiency and scalability. AI gateways are commonly used in industries such as healthcare, finance, and IoT to improve the functionality and accessibility of AI solutions. Compare and read user reviews of the best AI Gateways for Visual Studio Code currently available using the table below. This list is updated regularly.

  • 1
    Storm MCP

    Storm MCP

    Storm MCP

    Storm MCP is a gateway built around the Model Context Protocol (MCP) that lets AI applications connect to multiple verified MCP servers with one-click deployment, offering enterprise-grade security, observability, and simplified tool integration without requiring custom integration work. It enables you to standardize AI connections by exposing only selected tools from each MCP server, thereby reducing token usage and improving model tool selection. Through Lightning deployment, one can connect to over 30 secure MCP servers, while Storm handles OAuth-based access, full usage logs, rate limiting, and monitoring. It’s designed to bridge AI agents with external context sources in a secure, managed fashion, letting developers avoid building and maintaining MCP servers themselves. Built for AI agent developers, workflow builders, and indie hackers, Storm MCP positions itself as a composable, configurable API gateway that abstracts away infrastructure overhead and provides reliable context.
    Starting Price: $29 per month
  • 2
    Devant
    WSO2 Devant is an AI-native integration platform as a service designed to help enterprises connect, integrate, and build intelligent applications across systems, data sources, and AI services in the AI era. It enables users to connect to generative AI models, vector databases, and AI agents, and infuse applications with AI capabilities while simplifying complex integration challenges. Devant includes a no-code/low-code and pro-code development experience with AI-assisted development tools such as natural-language-based code generation, suggestions, automated data mapping, and testing to speed up integration workflows and foster business-IT collaboration. It provides an extensive library of connectors and templates to orchestrate integrations across protocols like REST, GraphQL, gRPC, WebSockets, TCP, and more, scale across hybrid/multi-cloud environments, and connect systems, databases, and AI agents.
    Starting Price: Free
  • 3
    Grafbase

    Grafbase

    Grafbase

    Grafbase is a high-performance GraphQL platform designed to help developers build, unify, and manage APIs by combining multiple data sources into a single federated API layer. It acts as a GraphQL federation gateway that aggregates services such as databases, microservices, REST APIs, and third-party systems into one unified endpoint that applications can query efficiently. Developers can compose a federated graph from multiple independent subgraphs, allowing different teams or services to evolve independently while still presenting a single coherent API to clients. Grafbase includes a schema registry and governance tools that enable teams to manage schema changes, run checks to detect breaking changes, and collaborate on schema proposals before deployment. It also provides analytics, observability, and performance monitoring features that track API usage and help teams optimize their data infrastructure.
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