Skip to main content
Glama
prodbeam

Prodbeam MCP Server

by prodbeam

setup_team

Set up a team by providing its name and member email addresses; automatically discovers GitHub usernames, Jira accounts, active repos, projects, and sprints.

Instructions

One-time team setup. Provide team name and member emails — prodbeam auto-discovers GitHub usernames, Jira accounts, active repos, projects, and sprints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailsYesEmail addresses of team members
teamNameYesTeam name (e.g., "Platform Engineering")
Behavior2/5

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

With no annotations provided, the description carries full burden of behavioral disclosure. It reveals that the tool auto-discovers additional data beyond inputs, but it omits critical safety information such as whether the operation is destructive, whether it can be run multiple times, or if it requires special permissions. A more complete description would address these points.

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 sentence that front-loads the core purpose ('One-time team setup') and then provides additional context. It is appropriately concise with no wasted words, though breaking into two sentences could improve readability.

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?

For a simple tool with two required string parameters and no output schema, the description covers the main intent and what happens (auto-discovery). However, it leaves gaps such as what the tool returns, error scenarios, and whether the setup can be repeated. With no output schema, a brief note on expected results would improve completeness.

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

Parameters3/5

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

The schema already describes both parameters (teamName and emails) with 100% coverage. The description adds little extra meaning beyond restating the inputs and explaining the auto-discovery behavior, which is not parameter-specific. According to the guidelines, with high schema coverage, baseline is 3, and the description does not significantly elevate it.

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's purpose as 'One-time team setup' with specific inputs (team name and emails) and outputs (auto-discovery of GitHub usernames, Jira accounts, etc.). It is a specific verb+resource combination that distinguishes itself from sibling tools like sprint_retro or get_capabilities, which have different functions.

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

Usage Guidelines3/5

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

The description implies that this tool is for initial team setup only, but it does not explicitly state when not to use it or mention alternatives. Sibling tools are different enough that confusion is unlikely, but the description lacks explicit guidance on usage context or prerequisites.

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/prodbeam/prodbeam-mcp'

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