Skip to main content
Glama
Sign In
Telegram MCP Enhanced

Telegram MCP Enhanced

by sahajp0618-pixel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_draft

Retrieves the draft message for a Telegram chat, username, phone number, or 'me'; returns an empty string when no draft exists.

Instructions

Get the draft message for a specific entity.

Finds the draft message for an entity specified by username, chat_id,
phone number, or 'me'.

!IMPORTANT: If the entity is not found, it will return an error message.
If you are not sure about the entity, use the `search_dialogs`
tool and ask the user to select the correct entity from the list.

Args:
    entity (`str`):
        The identifier of the entity to get the draft message for.
        This can be a Telegram chat ID, a username, a phone number, or 'me'.

Returns:
    `str`:
        The draft message (empty string if no draft) for the specific entity
        or an error message if request failed.

Input Schema

NameRequiredDescriptionDefault
entityYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden and does well: it discloses that an unknown entity returns an error message rather than raising or returning empty, and that a missing draft yields an empty string. It does not discuss permissions or rate limits, but for a read operation this is solid disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The key behavior and the escape hatch are front-loaded and bolded, which is good. However, the Args/Returns docstring duplicates the prose above and restates return values that the output schema already covers, adding bulk without new information.

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

Completeness4/5

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

Given a single-parameter tool with an output schema, the description covers the input formats, the empty-draft case, the error case, and the recovery path. An agent could call this correctly from the description alone; only edge-format details are absent.

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 description coverage is 0% and the single property is a bare string, so the description must compensate; it enumerates the accepted identifier forms (chat ID, username, phone number, 'me'). That is meaningful added semantics, though it does not explain formatting nuances such as country-code expectations for phone numbers.

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?

States a specific verb and resource: 'Get the draft message for a specific entity.' This is clearly distinct from siblings like set_draft and get_messages, so an agent can pick it 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?

Gives concrete guidance for the failure case: if the entity is uncertain, use `search_dialogs` and ask the user to select the correct entity. It does not contrast with `get_messages` or `set_draft`, but the when-to-use context for the uncertain-entity case is explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools