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Discourse MCP

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Get Chat Messages

discourse_get_chat_messages

Retrieve chat channel messages with pagination, date filtering, or from last read position to access conversation history efficiently.

Instructions

Get messages from a chat channel with flexible pagination and date-based filtering. Supports: (1) paginating with direction='past'/'future' from a target_message_id, (2) querying messages around a specific target_date, (3) getting messages around a target_message_id, or (4) fetching from last read position.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channel_idYesThe chat channel ID
page_sizeNoNumber of messages to return (default: 50, max: 500)
target_message_idNoMessage ID to query around or paginate from
directionNoPagination direction: 'past' for older messages (DESC), 'future' for newer messages (ASC)
target_dateNoISO 8601 date string (e.g., '2024-01-15' or '2024-01-15T10:30:00Z') to query messages around that date
fetch_from_last_readNoIf true, start from the user's last read message
include_target_message_idNoWhether to include the target message in results (default: true)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions 'flexible pagination' and the four query modes, which gives some behavioral context. However, it lacks details on permissions, rate limits, error conditions, or response format (especially important since there's no output schema), leaving gaps for a mutation-free read operation.

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 front-loaded with the core purpose, followed by a bullet-like list of four specific capabilities. Every sentence directly contributes to understanding the tool's functionality, with zero redundant or vague language.

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 read operation with 7 parameters and no annotations or output schema, the description is adequate but incomplete. It covers the query modes well but omits details on permissions, rate limits, error handling, and return format. Given the complexity and lack of structured data, it should provide more behavioral context to be fully complete.

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 fully documents all 7 parameters. The description adds value by summarizing the four query modes, which helps contextualize parameters like target_message_id, direction, and fetch_from_last_read. However, it doesn't provide additional syntax or format details beyond the schema, meeting the baseline for high coverage.

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 verb ('Get') and resource ('messages from a chat channel'), and specifies the key capabilities: pagination and date-based filtering. It distinguishes itself from siblings like discourse_list_chat_channels (which lists channels) and discourse_search (which searches content) by focusing specifically on retrieving messages within a channel.

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 explicitly lists four usage scenarios (pagination, date-based query, message-based query, last-read fetch), providing clear context for when to use this tool. However, it does not mention when NOT to use it or explicitly name alternatives (e.g., discourse_search for broader content search), which prevents a perfect score.

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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