Fuul MCP Server

get_trigger

Retrieve a trigger row by its UUID, returning either draft or published copy without resolving project metadata.

Instructions

Gets one trigger row by UUID: GET /api/v1/projects/:projectId/triggers/:triggerId. Returns whichever row that UUID points to (draft or published copy). Does not resolve project.metadata_id. Prefer get_project or get_incentive triggers[] for draft_trigger_id vs published_trigger_id by ref. Example: {"project_id":"","trigger_id":""}.

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": {
      "project_id": "<project_id>",
      "trigger_id": "<trigger_id>"
    },
    "name": "get_trigger"
  }
}

Input Schema

Name	Required	Description	Default
`project_id`	Yes
`trigger_id`	Yes	Trigger UUID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.12.0May 30, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns whichever row (draft or published) and does not resolve metadata_id, and gives an example. However, it does not mention authentication requirements or potential errors, which would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, three sentences long, with the core purpose in the first sentence. Every sentence provides necessary information without redundancy.

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 simple get tool, the description covers the return behavior (draft vs published), a key limitation (no metadata_id resolution), and provides an example. Lacks mention of error handling or output schema, but the context is sufficient for an AI agent to use correctly.

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 describes project_id as uuid and trigger_id as uuid with description 'Trigger UUID'. The tool description adds context about the endpoint and provides an example with both UUIDs. With 50% schema coverage, the description adds some value but does not deeply elaborate on parameter meaning 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 the tool gets a trigger row by UUID, specifies the HTTP method and endpoint, and distinguishes that it returns either draft or published copy. It also provides differentiation from sibling tools by suggesting alternatives for draft_trigger_id vs published_trigger_id.

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

Usage Guidelines5/5

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

The description explicitly explains that the tool does not resolve project.metadata_id and suggests using get_project or get_incentive with triggers[] instead for related lookups. This gives clear when-to-use and when-not-to-use guidance.

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