Skip to main content
Glama

send_contact

Send a phone contact to a Telegram chat using the target chat ID, phone number, and first name. Optionally include last name or send silently.

Instructions

Send a phone contact to a Telegram chat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chat_idYesTarget chat ID.
phone_numberYesContact's phone number.
first_nameYesContact's first name.
last_nameNoContact's last name.
disable_notificationNoSend silently.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
errorNo
message_idNo
chat_idNo

Implementation Reference

  • The send_contact MCP tool handler. Registered dynamically via @mcp.tool decorator within register_media_tools(). Sends a phone contact using ctx.bot.send_contact(), with chat allowance check, rate limiting, audit logging, and error handling.
    if allowed_tools is None or "send_contact" in allowed_tools:
    
        @mcp.tool
        async def send_contact(
            chat_id: int,
            phone_number: str,
            first_name: str,
            last_name: str | None = None,
            disable_notification: bool = False,
        ) -> SendMediaResult:
            """Send a phone contact to a Telegram chat.
    
            Args:
                chat_id: Target chat ID.
                phone_number: Contact's phone number.
                first_name: Contact's first name.
                last_name: Contact's last name.
                disable_notification: Send silently.
            """
            if not ctx.is_chat_allowed(chat_id):
                result = SendMediaResult(ok=False, error=f"Chat {chat_id} is not allowed.")
                if ctx.audit_logger:
                    ctx.audit_logger.log(
                        "send_contact",
                        {"chat_id": chat_id, "phone_number": phone_number},
                        result.ok,
                        result.error,
                    )
                return result
    
            try:
                if ctx.rate_limiter:
                    await ctx.rate_limiter.acquire()
                msg = await ctx.bot.send_contact(
                    chat_id=chat_id,
                    phone_number=phone_number,
                    first_name=first_name,
                    last_name=last_name,
                    disable_notification=disable_notification,
                )
                result = SendMediaResult(ok=True, message_id=msg.message_id, chat_id=msg.chat.id)
            except (TelegramBadRequest, TelegramForbiddenError) as exc:
                result = SendMediaResult(ok=False, error=str(exc))
    
            if ctx.audit_logger:
                ctx.audit_logger.log(
                    "send_contact",
                    {"chat_id": chat_id, "phone_number": phone_number},
                    result.ok,
                    result.error,
                )
            return result
  • SendMediaResult schema: Pydantic model extending ToolResponse with message_id and chat_id fields.
    class SendMediaResult(ToolResponse):
        message_id: int | None = None
        chat_id: int | None = None
  • Permission registration: 'send_contact' is mapped to PermissionLevel.MESSAGING.
    "send_contact": PermissionLevel.MESSAGING,
  • register_media_tools function signature: orchestrates registration of all media tools including send_contact.
    def register_media_tools(
        mcp: FastMCP, ctx: BotContext, allowed_tools: set[str] | None = None
    ) -> None:
  • Import of register_media_tools from aiogram_mcp/tools/media.py, called at server startup.
    from .tools.media import register_media_tools
Behavior2/5

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

With no annotations, the description carries full burden but only states the basic action. It does not disclose effects (e.g., whether it sends silently, whether it requires permission, or what the response contains), leaving the agent without critical behavioral context.

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 description is a single sentence front-loading the key information. No wasted words, though it could benefit from slight expansion.

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?

Given the existence of an output schema, return values are covered. However, the description lacks behavioral and usage context for a mutation tool. More information (e.g., silent sending, permissions) would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for each parameter, so baseline is 3. The description adds no extra meaning beyond the 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 it sends a phone contact to a Telegram chat, using a specific verb and resource. This distinguishes it from sibling tools that send other media types (e.g., send_photo, send_audio).

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?

No guidance is provided on when to use this tool versus alternatives (e.g., sending a message with a contact file). There are no notes on prerequisites or limitations.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Py2755/aiogram-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server