Veai Veai Veai AI Agent is an IDE-native AI agent that debugs, refactors, and tests through your JetBrains IDE — not through terminal commands — saving tokens by using IDE facts instead of noisy logs. Built for developers in large, complex codebases.

The agent uses IDE indexes, debugger state, and coverage data instead of dumping logs and grepping files — so it spends your tokens on answers, not on reading code the IDE already understands. Less noise, lower cost, faster results.

IDE-native debugging, refactoring, and testing

  • Debug with real execution data: investigate failures with debugger state, stack traces, executed instructions, and data flow instead of adding log statements by hand.
  • Refactor semantically: search symbols, find usages, rename, and update code through IDE indexes and refactorings, not grep-based edits that break cross-file references.
  • Generate tests with coverage feedback: create or update unit, integration, and end-to-end tests, then use IDE coverage and branch-aware analysis to target uncovered paths.
  • Find and fix security vulnerabilities: scan JVM projects for vulnerabilities with detailed findings and agent-assisted fixes.
  • Fix quality issues in context: use inspections, quick fixes, library decompilation, and build/test results from the IDE.
  • Keep your workflow native: run configurations, test runners, web search, webpage reading, and Allure TestOps data are available directly from the agent.

Use it for

  • debugging with IDE execution data and stack traces
  • generating tests with coverage feedback and detecting flaky tests
  • finding and fixing security vulnerabilities (SAST)
  • refactoring code with IDE-aware search and safe renames
  • fixing pull request feedback, stack traces, test failures, and TMS-linked issues
  • building features and microservices from specifications
  • migrating code to new frameworks or library versions
  • generating documentation and code comments

Open standards and team controls

  • MCP and AGENTS.md support for portable AI workflows.
  • Bring-your-own-key (BYOK) LLM support and edit-scope controls for teams.
  • Enterprise: VPC deployment, self-hosting, and SSO.

Agent modes

General, Code, Test, Plan, Review, and Debug modes — each mode leverages IDE-specific tools (Debug mode runs the debugger, Test mode reads coverage data). Plus an Orchestrator that splits complex tasks across specialized subagents, and custom modes for team workflows.

Getting started

  1. Install Veai AI Agent.
  2. Open the agent from your JetBrains IDE.
  3. Try Debug mode to investigate a failing test — it uses the IDE debugger, not log prints.

Start coding with your IDE's full power. Watch a quick demo, or submit an issue if you find a bug or want to share feedback.

If Veai AI Agent helps your work, please rate the plugin on JetBrains Marketplace.

]]> What's New in Veai AI Agent 5.13
  • Test coverage in WebStorm and PyCharm: generate tests from editor gutter icons for JavaScript, TypeScript, and Python — not just JVM projects.
  • Files outside the project: the agent can now read and write files beyond the project root — useful for monorepos, shared configs, and neighboring repositories.
  • Project onboarding: a short onboarding flow sets up rules, skills, and MCP servers tailored to your project. The agent starts understanding your project from the first chat.
  • Editor ↔ Chat hotkey: press Ctrl+Shift+X, Tab to toggle focus between the editor and the agent chat — no mouse needed.
  • Performance: chat updates are faster and each message uses less memory, especially in long conversations.
  • UI fixes: plugin window stays open after closing a tab, model selector displays correctly, attachments no longer break when the source message is deleted, and Rider floating toolbar shows the add-selection action.
  • Agent and stability fixes: DeepSeek no longer crashes on tool calls, MCP results are no longer lost, and the agent can use the terminal alongside configuration tools. Fixed Rider file completion, UI freezes during highlighting, and subagent progress display.
]]> Veai Veai Veai AI Agent is an IDE-native AI agent that debugs, refactors, and tests through your JetBrains IDE — not through terminal commands — saving tokens by using IDE facts instead of noisy logs. Built for developers in large, complex codebases.

The agent uses IDE indexes, debugger state, and coverage data instead of dumping logs and grepping files — so it spends your tokens on answers, not on reading code the IDE already understands. Less noise, lower cost, faster results.

IDE-native debugging, refactoring, and testing

  • Debug with real execution data: investigate failures with debugger state, stack traces, executed instructions, and data flow instead of adding log statements by hand.
  • Refactor semantically: search symbols, find usages, rename, and update code through IDE indexes and refactorings, not grep-based edits that break cross-file references.
  • Generate tests with coverage feedback: create or update unit, integration, and end-to-end tests, then use IDE coverage and branch-aware analysis to target uncovered paths.
  • Find and fix security vulnerabilities: scan JVM projects for vulnerabilities with detailed findings and agent-assisted fixes.
  • Fix quality issues in context: use inspections, quick fixes, library decompilation, and build/test results from the IDE.
  • Keep your workflow native: run configurations, test runners, web search, webpage reading, and Allure TestOps data are available directly from the agent.

Use it for

  • debugging with IDE execution data and stack traces
  • generating tests with coverage feedback and detecting flaky tests
  • finding and fixing security vulnerabilities (SAST)
  • refactoring code with IDE-aware search and safe renames
  • fixing pull request feedback, stack traces, test failures, and TMS-linked issues
  • building features and microservices from specifications
  • migrating code to new frameworks or library versions
  • generating documentation and code comments

Open standards and team controls

  • MCP and AGENTS.md support for portable AI workflows.
  • Bring-your-own-key (BYOK) LLM support and edit-scope controls for teams.
  • Enterprise: VPC deployment, self-hosting, and SSO.

Agent modes

General, Code, Test, Plan, Review, and Debug modes — each mode leverages IDE-specific tools (Debug mode runs the debugger, Test mode reads coverage data). Plus an Orchestrator that splits complex tasks across specialized subagents, and custom modes for team workflows.

Getting started

  1. Install Veai AI Agent.
  2. Open the agent from your JetBrains IDE.
  3. Try Debug mode to investigate a failing test — it uses the IDE debugger, not log prints.

Start coding with your IDE's full power. Watch a quick demo, or submit an issue if you find a bug or want to share feedback.

If Veai AI Agent helps your work, please rate the plugin on JetBrains Marketplace.

]]> What's New in Veai AI Agent 5.13
  • Test coverage in WebStorm and PyCharm: generate tests from editor gutter icons for JavaScript, TypeScript, and Python — not just JVM projects.
  • Files outside the project: the agent can now read and write files beyond the project root — useful for monorepos, shared configs, and neighboring repositories.
  • Project onboarding: a short onboarding flow sets up rules, skills, and MCP servers tailored to your project. The agent starts understanding your project from the first chat.
  • Editor ↔ Chat hotkey: press Ctrl+Shift+X, Tab to toggle focus between the editor and the agent chat — no mouse needed.
  • Performance: chat updates are faster and each message uses less memory, especially in long conversations.
  • UI fixes: plugin window stays open after closing a tab, model selector displays correctly, attachments no longer break when the source message is deleted, and Rider floating toolbar shows the add-selection action.
  • Agent and stability fixes: DeepSeek no longer crashes on tool calls, MCP results are no longer lost, and the agent can use the terminal alongside configuration tools. Fixed Rider file completion, UI freezes during highlighting, and subagent progress display.
]]> Veai Veai Veai AI Agent is an IDE-native AI agent that debugs, refactors, and tests through your JetBrains IDE — not through terminal commands — saving tokens by using IDE facts instead of noisy logs. Built for developers in large, complex codebases.

The agent uses IDE indexes, debugger state, and coverage data instead of dumping logs and grepping files — so it spends your tokens on answers, not on reading code the IDE already understands. Less noise, lower cost, faster results.

IDE-native debugging, refactoring, and testing

  • Debug with real execution data: investigate failures with debugger state, stack traces, executed instructions, and data flow instead of adding log statements by hand.
  • Refactor semantically: search symbols, find usages, rename, and update code through IDE indexes and refactorings, not grep-based edits that break cross-file references.
  • Generate tests with coverage feedback: create or update unit, integration, and end-to-end tests, then use IDE coverage and branch-aware analysis to target uncovered paths.
  • Find and fix security vulnerabilities: scan JVM projects for vulnerabilities with detailed findings and agent-assisted fixes.
  • Fix quality issues in context: use inspections, quick fixes, library decompilation, and build/test results from the IDE.
  • Keep your workflow native: run configurations, test runners, web search, webpage reading, and Allure TestOps data are available directly from the agent.

Use it for

  • debugging with IDE execution data and stack traces
  • generating tests with coverage feedback and detecting flaky tests
  • finding and fixing security vulnerabilities (SAST)
  • refactoring code with IDE-aware search and safe renames
  • fixing pull request feedback, stack traces, test failures, and TMS-linked issues
  • building features and microservices from specifications
  • migrating code to new frameworks or library versions
  • generating documentation and code comments

Open standards and team controls

  • MCP and AGENTS.md support for portable AI workflows.
  • Bring-your-own-key (BYOK) LLM support and edit-scope controls for teams.
  • Enterprise: VPC deployment, self-hosting, and SSO.

Agent modes

General, Code, Test, Plan, Review, and Debug modes — each mode leverages IDE-specific tools (Debug mode runs the debugger, Test mode reads coverage data). Plus an Orchestrator that splits complex tasks across specialized subagents, and custom modes for team workflows.

Getting started

  1. Install Veai AI Agent.
  2. Open the agent from your JetBrains IDE.
  3. Try Debug mode to investigate a failing test — it uses the IDE debugger, not log prints.

Start coding with your IDE's full power. Watch a quick demo, or submit an issue if you find a bug or want to share feedback.

If Veai AI Agent helps your work, please rate the plugin on JetBrains Marketplace.

]]> What's New in Veai AI Agent 5.13
  • Test coverage in WebStorm and PyCharm: generate tests from editor gutter icons for JavaScript, TypeScript, and Python — not just JVM projects.
  • Files outside the project: the agent can now read and write files beyond the project root — useful for monorepos, shared configs, and neighboring repositories.
  • Project onboarding: a short onboarding flow sets up rules, skills, and MCP servers tailored to your project. The agent starts understanding your project from the first chat.
  • Editor ↔ Chat hotkey: press Ctrl+Shift+X, Tab to toggle focus between the editor and the agent chat — no mouse needed.
  • Performance: chat updates are faster and each message uses less memory, especially in long conversations.
  • UI fixes: plugin window stays open after closing a tab, model selector displays correctly, attachments no longer break when the source message is deleted, and Rider floating toolbar shows the add-selection action.
  • Agent and stability fixes: DeepSeek no longer crashes on tool calls, MCP results are no longer lost, and the agent can use the terminal alongside configuration tools. Fixed Rider file completion, UI freezes during highlighting, and subagent progress display.
]]> Veai Veai Veai AI Agent is an IDE-native AI agent that debugs, refactors, and tests through your JetBrains IDE — not through terminal commands — saving tokens by using IDE facts instead of noisy logs. Built for developers in large, complex codebases.

The agent uses IDE indexes, debugger state, and coverage data instead of dumping logs and grepping files — so it spends your tokens on answers, not on reading code the IDE already understands. Less noise, lower cost, faster results.

IDE-native debugging, refactoring, and testing

  • Debug with real execution data: investigate failures with debugger state, stack traces, executed instructions, and data flow instead of adding log statements by hand.
  • Refactor semantically: search symbols, find usages, rename, and update code through IDE indexes and refactorings, not grep-based edits that break cross-file references.
  • Generate tests with coverage feedback: create or update unit, integration, and end-to-end tests, then use IDE coverage and branch-aware analysis to target uncovered paths.
  • Find and fix security vulnerabilities: scan JVM projects for vulnerabilities with detailed findings and agent-assisted fixes.
  • Fix quality issues in context: use inspections, quick fixes, library decompilation, and build/test results from the IDE.
  • Keep your workflow native: run configurations, test runners, web search, webpage reading, and Allure TestOps data are available directly from the agent.

Use it for

  • debugging with IDE execution data and stack traces
  • generating tests with coverage feedback and detecting flaky tests
  • finding and fixing security vulnerabilities (SAST)
  • refactoring code with IDE-aware search and safe renames
  • fixing pull request feedback, stack traces, test failures, and TMS-linked issues
  • building features and microservices from specifications
  • migrating code to new frameworks or library versions
  • generating documentation and code comments

Open standards and team controls

  • MCP and AGENTS.md support for portable AI workflows.
  • Bring-your-own-key (BYOK) LLM support and edit-scope controls for teams.
  • Enterprise: VPC deployment, self-hosting, and SSO.

Agent modes

General, Code, Test, Plan, Review, and Debug modes — each mode leverages IDE-specific tools (Debug mode runs the debugger, Test mode reads coverage data). Plus an Orchestrator that splits complex tasks across specialized subagents, and custom modes for team workflows.

Getting started

  1. Install Veai AI Agent.
  2. Open the agent from your JetBrains IDE.
  3. Try Debug mode to investigate a failing test — it uses the IDE debugger, not log prints.

Start coding with your IDE's full power. Watch a quick demo, or submit an issue if you find a bug or want to share feedback.

If Veai AI Agent helps your work, please rate the plugin on JetBrains Marketplace.

]]> What's New in Veai AI Agent 5.13
  • Test coverage in WebStorm and PyCharm: generate tests from editor gutter icons for JavaScript, TypeScript, and Python — not just JVM projects.
  • Files outside the project: the agent can now read and write files beyond the project root — useful for monorepos, shared configs, and neighboring repositories.
  • Project onboarding: a short onboarding flow sets up rules, skills, and MCP servers tailored to your project. The agent starts understanding your project from the first chat.
  • Editor ↔ Chat hotkey: press Ctrl+Shift+X, Tab to toggle focus between the editor and the agent chat — no mouse needed.
  • Performance: chat updates are faster and each message uses less memory, especially in long conversations.
  • UI fixes: plugin window stays open after closing a tab, model selector displays correctly, attachments no longer break when the source message is deleted, and Rider floating toolbar shows the add-selection action.
  • Agent and stability fixes: DeepSeek no longer crashes on tool calls, MCP results are no longer lost, and the agent can use the terminal alongside configuration tools. Fixed Rider file completion, UI freezes during highlighting, and subagent progress display.
]]> Veai Veai Veai AI Agent for coding, testing, and debugging, understands the project structure and follows its style.

Key features:

  • Agents use all IDE tooling: code coverage, refactorings, build, configuration, and test runner, decompilation, and quick fixes, while other AI tools can only edit files and run terminal commands
  • Combines the full power of precise IDE indexes with the semantic abilities of RAG for project structure, while other AI tools rely solely on fuzzy RAG
  • Provides agent modes: Agent, Ask, Tester, Plan, and Review
  • Supports open standards: MCP, AGENTS.md, Skills, Rules
  • Searches the web and reads webpages directly from the IDE
  • Integrates natively with Allure TestOps TMS

Key advantages over prompt-only tools:

  • For code search and refactorings: uses stable IDE internal tooling
  • For test generation: uses IDE coverage tooling and our complex technology (symbolic execution) to ensure that coverage is increased
  • For debugging: natively observes executed instructions and data flow (using code instrumentation)

Agent modes:

  • Agent – a full-fledged agent that can read and edit files. Best suited for day-to-day work, not related to project exploration and testing.
  • Ask – read-only agent mode: it can read files in the project, read pages on the internet. Best suited for project exploration tasks, brainstorming implementation ideas, and analyzing the causes of bugs.
  • Tester – mode focused on test generation. Although you can generate tests in Agent mode, this mode will provide better results.
  • Plan – the agent drafts and aligns a step-by-step plan with you before applying code changes.
  • Review – a mode focused on reviewing changes and providing feedback on diffs.

Veai AI Agent helps you:

  • generate microservices from specifications
  • migrate code to new frameworks or library versions
  • generate documentation and code comments
  • fix pull request review feedback
  • refactor and optimize code
  • fix failures using stacktraces or TMS data
  • generate unit, integration, and end-to-end tests
  • increase test coverage to pass quality gate requirements
  • update tests after implementation changes
  • detect and fix flaky tests

Search keywords: AI coding assistant, IntelliJ AI agent, JetBrains AI plugin, AI pair programming, AI programming assistant, AI code generator, AI debugging assistant, Debugging AI plugin, Stacktrace analysis, Bug fixing AI, Code debugging tool, Debugging assistant plugin, AI debugger, Error analysis plugin, Test generation plugin, Unit test generation, Test coverage improvement, Automated testing plugin, Flaky test detection, Code refactoring plugin, Code generation plugin, Automated code fixes, Code quality plugin, Code analysis plugin, IntelliJ IDEA plugin, JetBrains platform, Java AI assistant, Kotlin AI plugin, MCP servers integration, GitLab AI assistant, Development productivity plugin

If you enjoy using Veai AI Agent, please rate the plugin, share your feedback, and help us spread the word.

User Agreement

Very quick demo how to use Veai AI Agent.

Found a bug? Want to share your feedback? Submit an issue.

]]> What's New in Veai AI Agent 5.11

Veai AI Agent 5.11 improves everyday AI-assisted development in the IDE: scans JVM projects for vulnerabilities, runs tests with IDE context, keeps long chats working, and connects larger MCP toolsets more reliably.

  • Vulnerability search for JVM projects with findings, traces, explanations, and agent-assisted fixes.
  • IDE-based test execution in Rider and WebStorm, in addition to IntelliJ IDEA and PyCharm.
  • MCP server support through subagents for large toolsets.
  • LLM-based chat history summarization for longer agent sessions.
  • Improved library code reading for more accurate API usage and fewer guesses.
]]> Veai Veai Veai with an AI agent for coding, testing, and debugging, understands the project structure and follows its style.

Key features:

  • AI agent for coding, testing, and debugging
  • MCP servers support (GitLab, Jira, Confluence etc.)
  • Rules and Workflows support
  • Unit and integration tests generation
  • Test generation from execution
  • Flaky tests analysis

Veai helps you:

  • Generate microservices from specifications
  • Migrate code to new frameworks or library versions
  • Generate documentation and code comments
  • Fix pull request review feedback
  • Refactor and optimize code
  • Fix failures using stacktraces or TMS data
  • Generate unit, integration, and end-to-end tests
  • Increase test coverage to pass quality gate requirements
  • Update tests after implementation changes
  • Detect and fix flaky tests

]]>