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fivetran

Fivetran MCP Server

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by fivetran

transformation_projects_read

Retrieves Fivetran transformation project data by listing all projects or fetching specific details. Use this to query project information with read-only endpoints.

Instructions

Read operations on Fivetran transformation projects (2 endpoints: list_all_transformation_projects, transformation_project_details). Pass the endpoint name in name. Call list_endpoints(category='transformation-projects') for the full list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoRequest body — dict or JSON string. Required for POST/PATCH endpoints.
nameYesEndpoint name within this resource:action group (from list_endpoints).
queryNoQuery-string parameters.
path_paramsNoValues for path placeholders like {connectionId}, {groupId}.
Install Server

TDQS

A4/5.0
Behavior3/5

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

The phrase 'Read operations' makes clear this is non-destructive, which is valuable given zero annotations. However, it does not disclose any additional behavioral traits such as auth requirements, rate limits, response shape, or how the two endpoints differ in behavior.

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 two sentences long, front-loads the core purpose, and every sentence adds useful information. There is no waste or unnecessary repetition.

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?

Given the generic endpoint-router schema and no output schema, the description provides sufficient context by naming the two available endpoints and pointing to list_endpoints for full discovery. It could be more complete by describing what each endpoint returns or what path params are required, but the guidance is adequate for an agent to proceed.

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 coverage is 100%, so the baseline is 3. The description adds the specific category value 'transformation-projects' for list_endpoints and reiterates the `name` parameter usage, but it does not add meaningful semantics for `body`, `query`, or `path_params` beyond what the schema already states.

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 identifies this as a read-only tool for Fivetran transformation projects and names the two exact endpoints it covers (list_all_transformation_projects, transformation_project_details). This is specific enough to distinguish it from sibling read tools like transformations_read.

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?

It gives direct usage instructions: pass the endpoint name in `name` and call list_endpoints(category='transformation-projects') to get the full endpoint list. It clearly establishes the context for when to use this tool, though it doesn't explicitly mention alternative tools for non-read operations.

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

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