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# SmartBear Tightens Integration Between AI Coding and Testing Tools

**[DevOps.com](https://daily.dev/sources/devops)** · 3 min read · 0 upvotes · 0 comments

## Summary

SmartBear is integrating its testing platform with AI coding tools from Anthropic, GitHub, AWS, and Atlassian to bring testing directly into the IDE. Key additions include an MCP server for GitHub and connectors to ReadyAPI and Swagger for Claude Code users. The goal is to reduce friction and technical debt as AI-generated code volumes grow rapidly. Analysts note that verification outside the agent loop accumulates as 'verification debt,' and that using the same LLM to test its own code is ineffective — a separate model should review AI-generated code. A Futurum Group survey found 37% of organizations have already adopted AI-assisted testing.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://devops.com/smartbear-tightens-integration-between-ai-coding-and-testing-tools>

## Questions this post answers

### What new integrations did SmartBear add to connect testing with AI coding tools like Claude Code and GitHub?

SmartBear added a Model Context Protocol (MCP) server for GitHub and connectors to ReadyAPI and Swagger for developers using Claude Code from Anthropic, alongside integrations with AWS and Atlassian AI coding tools. These let developers test code directly inside the IDE where AI assistants generate it, rather than switching tools to validate output.

_daily.dev helps developers weighing new AI-testing integrations track how tools like SmartBear connect to their coding stack._

### Why should you use a different LLM to review AI-generated code than the one that wrote it?

Using the same large language model to both write and review code is essentially asking it to grade its own homework, since it may not catch its own blind spots or errors. Software engineering teams are advised to base the code-reviewing AI agent on a different LLM than the one used for code generation, improving the odds of catching real issues.

_developers building AI review pipelines can follow guidance like this on daily.dev before picking their reviewer model._

### What percentage of organizations have adopted AI-assisted testing?

A Futurum Group survey found that well over a third of organizations, 37%, have adopted AI-assisted testing. The same research frames AI as now overtaking traditional development approaches as the top driver for software delivery, underscoring pressure on teams to catch up on validating AI-generated code before it enters a build.

_teams benchmarking their AI-testing adoption against peers can track surveys like this on daily.dev._

## Similar posts on daily.dev

- [SmartBear Delivers AI Enhancements Across Entire Software Application Testing Lifecycle](https://daily.dev/posts/smartbear-delivers-ai-enhancements-across-entire-software-application-testing-lifecycle-0lpqububr) · SD Times · 0 upvotes · 0 comments
- [SmartBear’s Swagger update targets the API drift problem AI coding tools created](https://daily.dev/posts/smartbear-s-swagger-update-targets-the-api-drift-problem-ai-coding-tools-created-5scbx9kyb) · The New Stack · 0 upvotes · 0 comments
- [SmartBear Adds Computer Vision Capability to Testing Platform](https://daily.dev/posts/smartbear-adds-computer-vision-capability-to-testing-platform-wtrmtoar8) · DevOps.com · 0 upvotes · 0 comments

---

Tags: [#ai-coding](https://daily.dev/tags/ai-coding), [#mcp](https://daily.dev/tags/mcp)

[View this post on daily.dev](https://daily.dev/posts/smartbear-tightens-integration-between-ai-coding-and-testing-tools-rrqvorqxr)

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