BotGauge MCP: Connect Your AI Assistant to Autonomous QA
BotGauge MCP connects BotGauge's autonomous QA engine directly to the AI tools your team already uses, so testing becomes something you simply ask for rather than a separate dashboard you have to visit.
What is MCP?
The Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to software, tools, and data through a standardized interface. Instead of building custom integrations for every application, AI agents can use MCP to discover and invoke the capabilities they need using natural language.
BotGauge MCP brings BotGauge's autonomous QA platform into your AI assistant. Once connected to an MCP-compatible client, your agent can generate test cases, execute end-to-end tests, investigate failures, and retrieve test insights using natural language, without writing automation scripts or switching between dashboards.
What You Can Do
With BotGauge MCP, testing becomes as simple as asking. Your AI assistant can autonomously generate test cases, execute end-to-end tests, analyze failures, and surface actionable insights, without requiring test scripts or manual intervention.
Generate Test Cases
Generate comprehensive end-to-end test cases from product requirements, user stories, or demo videos.
Browse Test Cases
Review all test cases across your test suites, filtered by feature, status, or execution history, directly from your AI assistant.
Bulk Modify Test Cases
Bulk update or modify test cases, change priorities, tags, ownership, or test steps across multiple cases at once without opening the dashboard.
Execute Test Runs
Execute autonomous test runs without writing automated scripts.
Validate Features
Validate new features before release by having your AI assistant test the expected user journeys.
Investigate Failures
Investigate failures faster with AI-generated root cause analysis, execution logs, screenshots, and recommendations.
Review Coverage
Review test coverage and execution insights to understand what was tested, what failed, and where risks remain.
On-Demand Testing
Run regression, smoke, or feature-specific tests on demand through simple conversational prompts.
Custom Bug Reports
Generate custom bug reports from failed test runs with configurable fields so the reports match your team's existing bug-tracking format.
Manage QA Workflow
Manage your QA workflow without switching between dashboards or interacting with APIs.
Generate Test Cases
Generate comprehensive end-to-end test cases from product requirements, user stories, or demo videos.
Browse Test Cases
Review all test cases across your test suites, filtered by feature, status, or execution history, directly from your AI assistant.
Bulk Modify Test Cases
Bulk update or modify test cases, change priorities, tags, ownership, or test steps across multiple cases at once without opening the dashboard.
Execute Test Runs
Execute autonomous test runs without writing automated scripts.
Validate Features
Validate new features before release by having your AI assistant test the expected user journeys.
Investigate Failures
Investigate failures faster with AI-generated root cause analysis, execution logs, screenshots, and recommendations.
Review Coverage
Review test coverage and execution insights to understand what was tested, what failed, and where risks remain.
On-Demand Testing
Run regression, smoke, or feature-specific tests on demand through simple conversational prompts.
Custom Bug Reports
Generate custom bug reports from failed test runs with configurable fields so the reports match your team's existing bug-tracking format.
Manage QA Workflow
Manage your QA workflow without switching between dashboards or interacting with APIs.
Who It's For
BotGauge MCP is built for teams that want AI to own the entire testing lifecycle, from generating tests to validating releases.
Developers
Validate features as you build them, catch regressions early, and investigate failures directly from your AI assistant without interrupting your development workflow.
Engineering Leaders
Scale software quality without scaling QA effort. Give every engineer access to autonomous testing through the AI tools they already use.
Product Managers
Verify product requirements, validate user flows, and confirm release readiness using natural language rather than manual test execution.
AI-First Engineering Teams
Embed autonomous QA into AI-powered development workflows, enabling your AI assistants to validate applications throughout the software delivery lifecycle continuously.
Works With Your AI Assistant
BotGauge MCP works with any AI assistant that supports the Model Context Protocol (MCP). Popular MCP-compatible clients include:
Try BotGauge MCP
If your team already uses an AI assistant to help ship code, you're one connection away from getting it to help test that code too.
BotGauge MCP is currently in beta - reach out to the BotGauge team to get connected.