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AdsMCP

AdsMCP

by skynes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

ads_telegram_ai_chat_list

Lists saved public Telegram AI-related chats from the local catalog, defaulting to the Neron project and excluding participant data.

Instructions

List public Telegram AI-related chats saved in the local catalog; defaults to the Neron project and never returns participant data.

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": "ads_telegram_ai_chat_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
statusNo
chat_typeNo
project_idNoneron

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden; 'List' plus 'never returns participant data' usefully discloses a read-only, privacy-scoped operation, which is real added value. It omits pagination/limit behavior, ordering, and what happens when the project has no chats, so it is only partially transparent.

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?

A single compact sentence with the resource front-loaded and the two key constraints (default project, no participant data) appended. Nothing is redundant.

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

Completeness2/5

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

No annotations, no output schema, and four undocumented parameters mean the description should explain the filters and the return shape (e.g. list of chats with ids/names). It does neither, leaving an agent guessing how to narrow results and what fields come back.

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% across 4 parameters. The description only clarifies project_id's default and reinforces the privacy scope; the limit, status, and chat_type filters (two of them enums) are left entirely undocumented for filtering semantics such as default status inclusion.

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?

States a specific verb ('List') and a precise resource ('public Telegram AI-related chats saved in the local catalog'), which cleanly separates it from the write-side sibling ads_telegram_ai_chat_upsert. It does not name that sibling explicitly, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The default project ('Neron') gives context for a first call, and 'saved in the local catalog' implies this reads pre-registered chats rather than searching Telegram live. However, it never states when to prefer this over ads_telegram_ai_search_run_list or ads_tg_resource_list, so usage is only implied.

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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