Skip to main content
Glama
debugg-ai

Debugg AI MCP

Official
by debugg-ai

Project

project

Get, list, or create DebuggAI projects. Use actions to retrieve details by UUID, browse paginated summaries, or add new projects linked to GitHub repos and teams.

Instructions

Manage DebuggAI projects. Pass an "action":

  • "get" {uuid} → one project with full detail.

  • "list" {q?, page?, pageSize?} → paginated project summaries.

  • "create" {name, platform, (teamUuid|teamName), (repoUuid|repoName)} → create a project. The repo must be GitHub-linked; names resolve by case-insensitive exact match.

Note: there is no update/delete here — rename/delete a project from the DebuggAI web app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo[list] Free-text search.
nameNo[create] Project name.
pageNo[list] Page (1-indexed).
uuidNo[get] Project UUID.
actionYesOperation to perform.
pageSizeNo[list] Page size (1..200).
platformNo[create] Platform, e.g. "web".
repoNameNo[create] GitHub repo name "org/repo" (or repoUuid).
repoUuidNo[create] GitHub repo UUID (or repoName).
teamNameNo[create] Team name (or teamUuid).
teamUuidNo[create] Team UUID (or teamName).
Behavior5/5

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

The description adds value beyond annotations by detailing that 'create' requires the repo to be GitHub-linked and names resolve by case-insensitive exact match. Annotations indicate not read-only and not destructive, which aligns with the create action. No contradictions.

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 a single paragraph with a clear structure: an introductory sentence followed by bullet-style action definitions. It is concise and front-loaded, though a list or subheadings could improve scanability. No unnecessary words.

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?

For a tool with no output schema, the description adequately describes return types for each action (full detail vs. paginated summaries). It covers all actions and notes important constraints, but lacks details on error handling or pagination behavior beyond page/pageSize.

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

Parameters5/5

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

The input schema has 100% coverage with descriptions, but the description augments this by grouping parameters per action (e.g., (teamUuid|teamName)) and adding constraints like 'repo must be GitHub-linked'. This provides useful context beyond the 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 it manages DebuggAI projects and enumerates three distinct actions (get, list, create), each with a specific verb and resource. It explicitly notes that update/delete are not available, differentiating from any potential sibling tools for project mutation.

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 clear guidance on when to use each action (e.g., 'get' for full detail, 'list' for summaries) and explicitly states that update/delete are not available here, directing to the web app. While it doesn't compare directly to the listed sibling tools, the siblings are sufficiently different (e.g., executions, browser checks) that the usage context is clear.

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