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Debugg AI MCP

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by debugg-ai

Run E2E Browser Test

check_app_in_browser

Launch a live website or localhost app in a real browser to verify a task or check. Use for visual QA, flow validation, regression, or any test that requires actual browser interaction.

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.

CREDENTIALS: pass them as PARAMETERS, not only in the description. Naming an account in description alone does not make the agent use it — it falls back to the environment's stored credential. Use username/password (or credentialId) for the run's identity, auth.username/auth.password to pin the precondition login, and loginCredentials for accounts the agent must use at a login form it hits PART-WAY through the task (e.g. set a password → bounced to sign-in → log in as the account you just created). Anything you specify beats the environment's default for every login in the run; the result reports the identity actually used under logins.

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, then land on deepUrl. Use this instead of hoping the agent signs itself in at a login wall. Pass username/password here to pin WHICH account it authenticates as; omit them to use the environment's default credential.
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. Takes precedence over the environment's default credential for EVERY login in the run.
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.
freshSessionNoDefault false. Set true to force a REAL login instead of reusing the warm session the backend keeps per account. Use when the login flow itself is what you're checking, when you suspect the stored session is stale, or when the app's only route between personas is a logout. Costs one login; the run re-captures afterwards, so later runs stay fast.
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
loginCredentialsNoAccounts the agent may sign in as when it hits a login form DURING the task — not just the first login. Use this for flows that authenticate part-way through, e.g. set a password, get bounced to sign-in, then log in as the account you just provisioned. Stating credentials only in `description` is not enough: pass them here and the agent uses exactly these values. Overrides the environment's default credential.
useEnvironmentCredentialsNoDefault true. Set false to forbid the agent from ever auto-filling the environment's stored credentials — it signs in only as an account this call named (username/password, credentialId, credentialRole, loginCredentials, or auth.username), or not at all. Use when a run must prove a SPECIFIC account's experience and a silent fallback to the default test user would invalidate it.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv4.2.2
    • addedInput schema / properties / freshSession
      Added value: +{
      +  "description": "Default false. Set true to force a REAL login instead of reusing the warm session the backend keeps per account. Use when the login flow itself is what you're checking, when you suspect the stored session is stale, or when the app's only route between personas is a logout. Costs one login; the run re-captures afterwards, so later runs stay fast.",
      +  "type": "boolean"
      +}
  2. Changed6 schema fields changedv3.10.0
    • changedInput schema / properties / auth / description
      Previous value: -"Optional 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."New value: +"Optional auth-precondition for a 'log in THEN deep-navigate' check. Set precondition:'login' to authenticate first, then land on deepUrl. Use this instead of hoping the agent signs itself in at a login wall. Pass username/password here to pin WHICH account it authenticates as; omit them to use the environment's default credential."
    • addedInput schema / properties / auth / properties / password
      Added value: +{
      +  "description": "Password for auth.username.",
      +  "type": "string"
      +}
    • addedInput schema / properties / auth / properties / username
      Added value: +{
      +  "description": "Account to authenticate as for the precondition login. Overrides the environment's default credential.",
      +  "type": "string"
      +}
    • addedInput schema / properties / loginCredentials
      Added value: +{
      +  "description": "Accounts the agent may sign in as when it hits a login form DURING the task — not just the first login. Use this for flows that authenticate part-way through, e.g. set a password, get bounced to sign-in, then log in as the account you just provisioned. Stating credentials only in `description` is not enough: pass them here and the agent uses exactly these values. Overrides the environment's default credential.",
      +  "items": {
      +    "additionalProperties": false,
      +    "properties": {
      +      "label": {
      +        "description": "Optional human label (e.g. 'newly invited user') to disambiguate in the task text.",
      +        "type": "string"
      +      },
      +      "password": {
      +        "description": "That account's password.",
      +        "type": "string"
      +      },
      +      "username": {
      +        "description": "Account email/username to type into the login form.",
      +        "type": "string"
      +      }
      +    },
      +    "required": [
      +      "username",
      +      "password"
      +    ],
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
    • addedInput schema / properties / useEnvironmentCredentials
      Added value: +{
      +  "description": "Default true. Set false to forbid the agent from ever auto-filling the environment's stored credentials — it signs in only as an account this call named (username/password, credentialId, credentialRole, loginCredentials, or auth.username), or not at all. Use when a run must prove a SPECIFIC account's experience and a silent fallback to the default test user would invalidate it.",
      +  "type": "boolean"
      +}
    • changedInput schema / properties / username / description
      Previous value: -"A 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."New value: +"A 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. Takes precedence over the environment's default credential for EVERY login in the run."
  3. Addedv3.7.4
  4. Removedv3.7.2
  5. Changed1 schema field changedv3.7.0
    • addedInput schema / properties / auth
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "Optional 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.",
      +  "properties": {
      +    "deepUrl": {
      +      "description": "Optional URL to navigate to and evaluate AFTER login (e.g. a deep settings page). Falls back to `url` if omitted.",
      +      "type": "string"
      +    },
      +    "entryUrl": {
      +      "description": "Optional URL of the login page to authenticate on.",
      +      "type": "string"
      +    },
      +    "environmentId": {
      +      "description": "UUID of the environment whose credentials to log in with. See available environments in the tool description above.",
      +      "type": "string"
      +    },
      +    "precondition": {
      +      "description": "'login' = authenticate before evaluating; 'none' (default) = no login precondition.",
      +      "enum": [
      +        "login",
      +        "none"
      +      ],
      +      "type": "string"
      +    }
      +  },
      +  "type": "object"
      +}
  6. Addedv2.6.1

TDQS

A4.6/5.0
Behavior5/5

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

The description adds substantial behavior beyond the annotations (readOnlyHint:false, openWorldHint:true, destructiveHint:false): automatic localhost tunneling, the ~25-step agent budget and timeout risk, warm-session reuse vs freshSession forced real login, and the credential fallback behavior ('it falls back to the environment's stored credential'). It even discloses what the result reports (`logins` identity). This is rich, accurate transparency with no contradiction against annotations.

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 long but purpose-built for a genuinely complex tool (12 params, nested auth objects, credential governance). It is sensibly front-loaded: purpose, then localhost support, then scoping, then credentials. There is some redundancy between the credentials prose and the schema-level descriptions of auth/loginCredentials/useEnvironmentCredentials, but the prose earns its place by adding precedence semantics the schema lacks.

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

Completeness5/5

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

For a complex, credential-heavy tool with no output schema, the description covers the hard parts thoroughly: what the tool does, localhost tunneling, per-call scoping with a step budget, and the full matrix of credential mechanisms and their precedence. It even notes the output identity field (`logins`), compensating for the absent output schema. Nothing an agent needs to invoke it correctly is left unexplained.

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%, so the baseline is 3. The description adds real semantic value above the schema by explaining relationships and precedence among the credential parameters (username/password vs auth.username vs loginCredentials vs credentialId vs useEnvironmentCredentials), including when each applies (part-way login, precondition login, forbidding auto-fill). This inter-parameter guidance is not derivable from the schema text alone, justifying a 4.

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 states a specific purpose with concrete verbs and resource: 'Give an AI agent eyes on a live website or app... browses it, interacts with it, and tells you whether a given task or check passed.' It names clear use cases (visual QA, flow validation, regression checks) and qualifies itself as 'anything that needs a real browser to verify,' which helps separate it from sibling browser tools like probe_page and trigger_crawl. This goes well beyond a tautology.

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 gives explicit when-to-use context ('Use for visual QA, flow validation, regression checks, or anything that needs a real browser to verify') and unusually strong how-to guidance: one focused check per call, a ~25-step internal budget, advice to split multi-step flows into separate calls with a concrete three-call example. It lacks explicit exclusions and does not name sibling tools as alternatives, but the usage context is clear enough to be a solid 4.

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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