Best AI Gateways for Visual Studio Code

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

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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

Anaconda

Anaconda

Anaconda is an AI-native development platform that helps teams move from experimentation to production with trusted open-source packages, governed environments, and production-grade orchestration. The platform provides a secure foundation for Python, data science, machine learning, and AI development across the full model lifecycle. Anaconda Core helps teams manage complex Python dependencies with validated packages, automated security scanning, and intelligent conflict resolution. The Anaconda Platform supports governed AI development so organizations can reduce broken environments, stalled deployments, and unmanaged open-source risk. Its trusted distribution is used by millions of users, developers, contributors, organizations, and Fortune 500 companies. Built for enterprise AI teams, Anaconda helps organizations accelerate open-source AI innovation while maintaining control, security, and governance.

9 Ratings

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2

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

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3

Devant

WSO2

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

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4

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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5

Apigene

Apigene

Apigene MCP Gateway is the runtime layer that connects AI agents to APIs and MCP servers through the Model Context Protocol. It exposes agent tools, context, skills, and instructions as a single remote MCP endpoint that is fully managed and governed, making MCP native rather than experimental. Apigene provides the full agent foundation layer as one MCP Gateway, allowing agents to securely access APIs and MCP servers without custom glue code or framework-specific logic. Teams can build AI agents using chat, defining which APIs and MCP servers the agent can use, how it should reason, and how it should act without code. It supports intelligent tool selection, automatically matching the right API or MCP tool to each request, and multi-platform deployment across ChatGPT, Claude, Cursor, Gemini, VS Code, internal copilots, enterprise AI platforms, and custom apps.

Starting Price: $200 per month

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