Skip to main content
Glama

get_board

Read a kanban board and get its status columns plus every issue/PR card, including number, title, state, repo, labels, and column. Needs project_id obtained from list_boards.

Instructions

Read one board: its Status columns and every issue/PR card on it.

``project_id`` is the opaque node id from ``list_boards`` (e.g. ``PVT_…``).
Each card carries its ``number``, ``title``, ``state``, ``repo``, ``labels``
and the ``status_name`` column it sits in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.6/5.0
Behavior3/5

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

Annotations are not provided, so the description carries the full burden of behavioral disclosure. It describes the read operation and what data will be returned, which implies a safe, non-destructive action, but it does not mention potential errors, authentication requirements, or any other side effects or behaviors beyond the read.

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 reasonably sized and front-loaded: it immediately states the purpose, then provides essential parameter context, and lists the data returned. However, it includes some degree of detail that might be redundant given the output schema, but it still adds value.

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?

There is an output schema, so the description does not need to explain return values in depth, but it does anyway. With only one parameter and a clear description of what the tool returns, the description adequately covers what an agent needs to call the tool correctly, though it could capably mention error cases or prerequisites.

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?

With 0% schema description coverage, the description compensates by explaining that project_id is an opaque node ID from list_boards and providing an example format (e.g., PVT_...). This adds meaningful meaning and helps the agent know what value to supply.

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

Purpose4/5

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

The description clearly states the tool reads one board and its contents, using a specific verb ('Read') and resource ('one board'). It distinguishes itself from list_boards by referencing how to obtain the project_id, but does not explicitly differentiate from board_summary. The phrasing 'opaque node id from list_boards' clarifies its relationship to a sibling tool.

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 provides a clear context for usage by explaining that project_id comes from list_boards and giving an example format, but it does not explain when to use this tool versus board_summary or any exclusions. There is no explicit guidance on when not to use it.

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

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/lrivallain/precursor-kanban'

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