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Formbricks MCP by usefulapi

List survey responses

formbricks_list_responses
Read-only

List survey responses, optionally narrowed to one survey, one contact or a date window. This is the main read: the answers people gave. Formbricks v2: GET /management/responses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoHow many records to skip (offset paging).
limitNoPage size, 1-100.
orderNoSort direction.
sortByNoField to sort on, e.g. createdAt or updatedAt.
endDateNoISO-8601 upper bound on the date field.
surveyIdNoOnly responses to this survey.
contactIdNoOnly responses from this contact.
startDateNoISO-8601 lower bound on the date field.
filterDateFieldNoWhich date field the window applies to.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read, so the description's burden is reduced. It adds the concrete backend mapping (Formbricks v2: GET /management/responses) but says nothing about pagination behavior, default page size, or the shape/volume of what comes back – useful context that is absent.

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, front-loaded sentences with no filler; the core purpose leads and the endpoint detail trails. The endpoint sentence is marginally dev-facing rather than agent-facing, which keeps it short of a 5.

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 nine-parameter listing tool with no output schema, the description covers what it returns at a high level ('the answers people gave') but not the record shape or pagination semantics the agent needs to page correctly. Adequate but with a clear gap given the absent output schema.

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 all nine parameters, including paging and sort. The description reinforces the three filter axes (survey, contact, date window) but adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb and resource ('List survey responses') and immediately scopes it ('optionally narrowed to one survey, one contact or a date window'). It also carves itself out from the sibling read tools by declaring 'This is the main read: the answers people gave', which separates it from formbricks_get_response and formbricks_delete_response.

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 phrase 'This is the main read' implies when to reach for this tool, and the narrowing options signal the filter use cases. However, it never names an alternative (e.g. use formbricks_get_response for a single response) or states an exclusion, so the guidance stays implicit.

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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