Mike Vizard details how Kong’s integration of Model Context Protocol (MCP) into Insomnia 12 enhances support for AI-driven APIs by improving API testing, configuration, and security for DevOps teams.

Kong Adds Model Context Protocol Support to Insomnia API Tool

Author: Mike Vizard

Kong Inc. has introduced support for the Model Context Protocol (MCP) in Insomnia 12, its open source tool for designing, debugging, and testing APIs. MCP, developed by Anthropic, establishes a consistent protocol for artificial intelligence (AI) applications to access varied data sources. As MCP adoption grows, DevOps teams are expected to manage an increasing number of MCP clients and servers, boosting the need for reliable testing and security practices.

What is MCP?

The Model Context Protocol (MCP) is an emerging standard designed to streamline data access for AI agents, providing clarity and interoperability across large language models (LLMs) and AI services. MCP enables a uniform method for requesting and exchanging prompts, resources, and responses in distributed, AI-centric environments.

Insomnia 12: New Features for MCP

  • Native MCP Workflow Support: DevOps teams can now design, test, and debug MCP clients and servers directly from Insomnia using familiar API management workflows.
  • Direct MCP Server Connectivity: Users can connect directly to MCP servers, invoke tools and prompts with custom parameters, and inspect protocol- and authentication-level exchanges.
  • Mock Server Creation: Quickly spin up functional mock MCP servers from requirements, URLs, OpenAPI specs, or JSON samples—enabling fast prototyping in complex environments.
  • Automation and Git Integration: Insomnia 12 can automatically generate descriptive commit messages, manage logical file groupings, and synchronize sessions via Git Sync, allowing better version control across evolving MCP implementations.
  • Security and Compliance: Role-based access controls (RBAC) and compliance features help organizations address risks of misconfiguration and large-scale data exposure as AI adoption escalates.

Why MCP Matters for DevOps and AI

The rapid deployment of AI agents relying on MCP introduces new opportunities but also substantial challenges in configuration management and security. Insomnia’s integration of MCP targets these gaps, aiming to reduce the frequency and impact of mistakes—such as exposing sensitive data—that might be exploited by attackers if best practices are not established.

Looking Forward

MCP is still developing, with updates released quarterly. Kong has committed to maintaining compatibility in future Insomnia releases, so DevOps teams can keep pace with protocol changes without extra tooling burden. As the responsibilities for managing MCP infrastructure are clarified within organizations, tooling like Insomnia will play a crucial role in enabling secure, compliant, and effective AI-driven API ecosystems.

For additional details about MCP and Insomnia’s AI/DevOps integrations, visit Kong’s announcement or review the official Insomnia documentation.

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