@drmaxbdc/productboard-mcp

create_entity

Create a new Productboard entity with a type and matching field values. Call get_entity_configurations first to discover valid fields and schemas.

Instructions

Create a new Productboard entity. Call get_entity_configurations first to discover available fields for the entity type. The fields object should match the field schemas from configuration.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "type": "<type>",
      "fields": "<fields>"
    },
    "name": "create_entity"
  }
}

Input Schema

Name	Required	Description
`type`	Yes	Entity type to create
`fields`	Yes	Field values as JSON object. Use get_entity_configurations to discover available fields.
`relationships`	No	Optional relationships to create along with the entity

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.1Sep 13, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It states the fields must match configuration schemas but says nothing about permissions/auth, validation failure behavior, what the created entity response looks like, or effects on relationships. For a mutation tool with zero annotation coverage this is a significant gap.

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?

Three short sentences, front-loaded with the core action and the prerequisite immediately after. No filler, though the final sentence repeats the get_entity_configurations advice already given.

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?

Covers the creation action and the configuration prerequisite, but for a multi-entity-type mutation tool with nested relationship objects and no annotations or output schema, it leaves out validation behavior and return semantics that an agent would need.

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?

Schema description coverage is 100%, so the schema already documents type, fields, and relationships. The description reinforces the fields-vs-configuration relationship but adds no syntax, format, or constraint details beyond what the schema provides. Baseline 3 applies.

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?

States a specific verb and resource ('Create a new Productboard entity'), which is distinct from update_entity/delete_entity siblings. It doesn't explicitly contrast with siblings like update_entity, but the create action is unambiguous.

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?

Gives an explicit prerequisite and ordering: 'Call get_entity_configurations first to discover available fields for the entity type.' This is actionable guidance, though it doesn't mention when to choose this over alternatives or what happens on invalid input.

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