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line-desktop-mcp

line-desktop-mcp

by onlygummy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

List LINE chats

list_chats
Idempotent

List LINE chats with names, kinds, unread counts, and last previews to identify the conversation to read before fetching messages; nothing is marked as read.

Instructions

List your LINE chats with name, kind, unread count and last preview.

Call this before get_messages to find the chat you want. A direct chat is named after the other person; a group keeps its LINE name. Nothing is marked as read. The listing is cached for a few minutes and archived locally, so it still answers when LINE cannot be reached (stale: true says the data came from the archive). total counts the chats after filtering and before the limit; truncated is true when more chats exist than limit returned.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_chats"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryNoCase-insensitive substring filter on the chat name.
unread_onlyNoOnly chats that have unread messages.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv4.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations, it discloses that nothing is marked as read, that results are cached for a few minutes and archived locally, that the archive answers when LINE is unreachable, and that `stale: true` signals archived data. It also explains `total` and `truncated` semantics, which the annotations do not cover. The only mild tension is readOnlyHint=false against a purely listing operation, but the description never claims read-only status, so this is not a contradiction.

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 purpose and the call-ordering advice are front-loaded, and each subsequent sentence carries distinct information (naming convention, read-state behavior, caching, pagination fields). It is slightly dense with return-value detail that an output schema already covers, but nothing is redundant filler.

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?

For a three-parameter, zero-required listing tool with an output schema, the description covers purpose, sequencing, naming semantics, read-state side effects, cache/staleness behavior, and pagination fields. An agent has everything needed to call it correctly and interpret the response.

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?

Schema coverage is 67%: `query` and `unread_only` are documented in the schema, but `limit` is not. The description compensates by explaining that `total` counts chats after filtering and before the limit, and that `truncated` indicates more chats exist than `limit` returned, giving the agent the meaning of the limit boundary.

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 first sentence gives a specific verb and resource ("List your LINE chats") and enumerates the returned fields (name, kind, unread count, last preview), which immediately separates it from get_messages and search_messages. An agent can identify the tool without opening the schema.

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 explicitly sequences the tool: "Call this before `get_messages` to find the chat you want," which is actionable routing guidance. It does not, however, say when to prefer `search_messages` or `unread` instead, so the alternative-selection guidance is incomplete.

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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