Skip to main content
Glama
debugg-ai

Debugg AI MCP

Official
by debugg-ai

Test Suite

test_suite
Destructive

Manage test suites by listing, creating, running, retrieving results, or deleting. Identify suites via UUID or name with a project.

Instructions

Manage and run test suites. Identify a suite by suiteUuid, or suiteName + a project identifier (projectUuid|projectName). Pass an "action":

  • "list" {projectUuid|projectName, search?, page?, pageSize?} → paginated suites with status/pass-rate.

  • "create" {name, description, projectUuid|projectName} → create a suite.

  • "run" {suiteUuid|(suiteName+project), targetUrl?} → run all tests async. Poll with action:"results".

  • "results" {suiteUuid|(suiteName+project)} → suite + per-test outcomes.

  • "delete" {suiteUuid|(suiteName+project), confirm?} → soft-delete (DESTRUCTIVE; requires confirmation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo[create] Suite name.
pageNo[list] Page (1-indexed).
actionYesOperation to perform.
searchNo[list] Text filter over name/description.
confirmNo[delete] Set true to confirm deletion (when the client cannot prompt).
pageSizeNo[list] Page size (1..100).
suiteNameNoTest suite name (requires a project identifier).
suiteUuidNoTest suite UUID.
targetUrlNo[run] Override the default test target (full URL).
descriptionNo[create] Suite description.
projectNameNoProject name (or projectUuid).
projectUuidNoProject UUID (or projectName).
Behavior4/5

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

The annotations mark destructiveHint=true, and the description adds context by noting that the 'delete' action is a soft-delete that requires confirmation. It also discloses that 'run' executes tests asynchronously and suggests polling with the 'results' action. While the description does not detail all edge cases, it sufficiently complements the 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 structured with a clear introductory sentence followed by a bulleted list of actions. It is concise for the complexity (12 parameters) but could be slightly tighter by removing redundant phrasing (e.g., repeated identification pattern). Overall, it is well-organized and front-loaded.

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

Completeness3/5

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

Given the absence of an output schema and the tool's complexity (multiple actions, async behavior), the description covers identification and action parameters well but does not describe return values (e.g., paginated list format, test outcomes structure). Agents would need additional inference for expected outputs.

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?

The schema covers 100% of parameters with descriptions, but the description adds value by grouping parameters per action (e.g., [list] parameters, [create] parameters) and explaining composite identifiers like 'suiteName + a project identifier'. This reduces ambiguity beyond the raw schema.

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 'Manage and run test suites' and enumerates five specific actions (list, create, run, results, delete), each with distinct purposes. This distinguishes the tool from siblings like 'test_case' and 'executions' by focusing on test suite lifecycle management.

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 guidance on how to identify a suite (by UUID or name+project) and details each action's parameters. However, it does not explicitly contrast with sibling tools (e.g., when to use 'test_case' instead of 'test_suite') or state when not to use this tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/debugg-ai/debugg-ai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server