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Schimmilab

telegram-mcp-server

by Schimmilab

list_chats

Find Telegram chats by title, type, and unread count. Filter by substring and set result limit to locate chat IDs for other tools.

Instructions

List chats (groups, channels, direct messages).

Args: query: Optional case-insensitive substring filter on the chat title. When set, ALL dialogs are scanned so a match beyond the most-recent limit chats is still found (comparatively expensive, like title resolution); limit then caps the number of matches returned. limit: Max results (default 50, capped at 500). Without query this is also how many dialogs are fetched.

Returns objects with id, title, type ('group'/'channel'/'user'), unread. Use this to find a chat's id/title before calling other tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations exist, so description fully bears burden. Discloses that query makes scanning expensive, limit behavior with/without query, and return fields (id, title, type, unread). Adequate for a read-only list tool.

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?

Description is well-structured with Args section and clear sentences. Slightly verbose but not excessive; every sentence adds value.

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?

Covers purpose, parameter details, return structure, and usage context. No output schema but returns described. Complete given tool complexity and no annotations.

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 0%, but the description explains both parameters in detail: query as optional substring filter (expensive when set), limit default/cap and interaction with query. Adds substantial value beyond schema.

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 tool lists chats (groups, channels, direct messages) and distinguishes from siblings by noting its use to find chat IDs/titles before calling other tools.

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?

Provides clear context for use (find chat IDs/titles) and explains parameter behaviors (query scans all dialogs, limit caps results). No explicit when-not-to-use, but purpose is well-understood.

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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