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telegram-mcp

telegram-mcp

by draiqw
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

tg_chat_info

Get details for a Telegram chat or person: ID, username, type, member count, bio.

Instructions

Details about a chat or person: id, username, type, member count, bio.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "chat": "<chat>"
    },
    "name": "tg_chat_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
chatYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, but it only lists output fields and does not disclose potential errors, authentication requirements, rate limits, or side effects. While 'Details about' implies a read operation, this is not explicitly stated, and no behavioral context beyond the returned fields is provided.

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 a single, front-loaded sentence that efficiently communicates the tool's purpose and output fields with no filler. Every word contributes to understanding.

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?

The tool is simple (one parameter, output schema exists), and the description covers the purpose and expected output fields. However, it lacks input format details and usage guidance, which may lead to incorrect invocation, especially without annotations. It is minimally complete but has clear gaps.

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 description coverage is 0%, so the description must compensate. It clarifies that the 'chat' parameter can refer to a chat or a person, but it does not explain the expected format (e.g., numeric ID, username, phone number). This leaves important ambiguity for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns details about a chat or person, listing specific fields (id, username, type, member count, bio). This distinguishes it from sibling tools that handle participants, contacts, or bot-specific info, though it lacks an explicit verb like 'get' or 'fetch'.

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 implies the tool is used to fetch basic chat/person information, but it provides no explicit guidance on when to use it over alternatives or any exclusions/prerequisites. It does not mention relationship to sibling tools like tg_participants or tg_resolve.

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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