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Debugg AI MCP

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by debugg-ai

Run E2E Browser Test

check_app_in_browser

Use an AI agent to browse a live website or app and verify if a specific task or check passes. Supports localhost URLs automatically.

Instructions

Give an AI agent eyes on a live website or app. The agent browses it, interacts with it, and tells you whether a given task or check passed. Works on localhost or any URL. Use for visual QA, flow validation, regression checks, or anything that needs a real browser to verify.

LOCALHOST SUPPORT: Pass any localhost URL (e.g. http://localhost:3000) and it Just Works. A secure tunnel is automatically created so the remote browser can reach your local dev server — no manual ngrok setup, no port forwarding, no config.

SCOPE PER CALL: Keep each call to ONE focused check — a single page or a short interaction on a single screen (login, submit a form, verify a heading). For anything spanning multiple pages or long multi-step flows, split into SEPARATE calls — the remote browser agent has a ~25-step internal budget per call, and long single calls risk client-side timeouts. Example: instead of "log in, then go to settings, then update profile, then verify," make three calls: (1) log in & verify dashboard, (2) update settings, (3) verify profile change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to navigate to. Can be any public URL (https://example.com) OR a localhost/local dev server URL. For localhost URLs, a secure tunnel is automatically created — just make sure your dev server is running on that port.
authNoOptional auth-precondition for a 'log in THEN deep-navigate' check. Set precondition:'login' to authenticate first (using the environment's credentials), then land on deepUrl. Use this instead of hoping the agent signs itself in at a login wall.
passwordNoThe real password for the username above. Do NOT guess or use placeholder passwords — use credentials from the list above or ask the user.
repoNameNoGitHub repository name (e.g. 'my-org/my-repo'). Auto-detected from the current git repo — only provide this if you want to run against a different project than the one you're in.
usernameNoA real, existing account email for the target app. Do NOT invent or guess credentials — use one from the available credentials listed above, or ask the user. The browser agent will type this into the login form.
descriptionYesNatural language description of what to test or evaluate (e.g., 'Does the login form validate empty fields?' or 'Navigate to the homepage and verify the hero section loads')
credentialIdNoUUID of a specific credential to use for login. See available credentials in the tool description above.
environmentIdNoUUID of a specific environment to use for this test. See available environments in the tool description above.
credentialRoleNoPick a credential by role (e.g. 'admin', 'guest') from the resolved environment
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals key behaviors: automatic localhost tunneling, ~25-step budget per call, authentication options, and scope limitations. These details go beyond the annotations (readOnlyHint, openWorldHint, destructiveHint) and provide essential context for agent usage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured into sections (purpose, LOCALHOST SUPPORT, SCOPE PER CALL) with front-loaded key info. While slightly verbose, each sentence adds value, and the structure aids readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 params, nested objects, no output schema), the description covers most essential aspects: scope, localhost support, auth behavior, and example usage. It could be improved by briefly mentioning how results are returned, but overall it is complete enough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds meaningful context, especially for the 'auth' object (explaining deepUrl vs entryUrl) and credentials. It helps the agent understand when and how to use parameters effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gives an AI agent eyes on a live website, interact, and check pass/fail. It distinguishes from siblings (probe_page, trigger_crawl) by emphasizing full E2E interaction and verification, making its purpose specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage scenarios (visual QA, flow validation, regression checks) and advises splitting multi-step flows into separate calls due to step budget. While it doesn't directly compare to sibling tools, the guidance is practical and clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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