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chatwoot-mcp

by minholi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

chatwoot_get_csat_metrics

Read-only

Retrieve CSAT survey results with total responses, score breakdown, and response rate. Filter by period, inbox, or team to analyze customer satisfaction.

Instructions

Returns the aggregated CSAT summary: total responses, breakdown by score, and response rate.

Args:
    period: Analysis period.
    inbox_id: Filter by a specific inbox.
    team_id: Filter by a specific team.
    output_format: Output format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo30d
team_idNo
inbox_idNo
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already cover the safety profile with readOnlyHint=true and destructiveHint=false. The description adds useful aggregation context, but it does not disclose how filters combine or any access/rate implications beyond what annotations already imply. This is adequate but not rich.

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 short, front-loaded, and uses a clean Args block. Minor redundancy like 'Output format: Output format' prevents a perfect score, but overall it is appropriately sized.

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 simple read-only metrics call with optional parameters, enum defaults, and an output schema, the description is minimally sufficient for invocation. The main gap is lack of usage guidance relative to sibling CSAT tools, but an agent can likely call this tool correctly using schema defaults.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema property descriptions are absent (0% coverage), so the description must compensate. However, it only gives shallow labels such as 'Analysis period' and 'Output format,' which add little beyond the parameter names and enum values; only inbox_id and team_id gain any real meaning as filters.

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 opening sentence states a specific action ('Returns') and resource ('aggregated CSAT summary') with concrete components: total responses, breakdown by score, and response rate. This clearly differentiates it from the raw-response sibling chatwoot_get_csat_responses.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus the many sibling metrics tools, and it does not mention alternatives like chatwoot_get_csat_responses for raw data. The agent must infer selection solely from the tool name and the first sentence.

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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