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Chatwoot MCP Server

by mohnori

Get Chatwoot Conversation Details

chatwoot_get_conversation
Read-onlyIdempotent

Retrieve full details of a Chatwoot conversation by ID, including status, contact info, assignee, labels, and custom attributes. Get complete conversation data in markdown or JSON format.

Instructions

Get detailed information about a specific Chatwoot conversation.

This tool retrieves full details for a single conversation including contact info, assignee, labels, and custom attributes.

Args:

  • conversation_id (number): The ID of the conversation to retrieve (required)

  • response_format (string): Output format - "markdown" or "json" (default: "markdown")

Returns: Full conversation details including:

  • Status, inbox, and metadata

  • Complete contact information

  • Assignee details

  • Labels and custom attributes

  • Message statistics

Examples:

  • Get conversation details: { conversation_id: 123 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversation_idYesThe ID of the conversation
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds return content details (status, inbox, contact, assignee, labels, message stats), which enriches the behavioral profile beyond the annotation flags. No contradictions.

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 well-structured with Args, Returns, and Examples sections. The first sentence front-loads the purpose, and each section adds specific information without excess verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple read-only nature, the description covers purpose, parameters with defaults, return contents, and an example. No output schema exists, but the Returns section lists key fields. Annotations cover safety hints. This is complete for an agent to select and invoke correctly.

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

Parameters4/5

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

Both parameters are fully described in the schema (conversation_id, response_format). The description restates them and adds a usage example with conversation_id: 123, giving practical invocation context. Schema coverage is 100%, so the baseline is 3; the example lifts it to 4.

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 opens with 'Get detailed information about a specific Chatwoot conversation' and 'retrieves full details for a single conversation,' clearly distinguishing it from sibling tools that list or filter conversations. The verb 'Get' and resource 'specific conversation' are specific and 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?

The description states it is for a 'single conversation' and lists the contents (contact info, assignee, labels, custom attributes), implying use when you have a conversation ID. It does not explicitly mention alternatives like list_conversations, but the 'specific' scope provides context. No exclusions are stated.

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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