Skip to main content
Glama

list_phone_numbers

Retrieve all phone numbers linked to your ElevenLabs account for authentication and account management purposes.

Instructions

List all phone numbers associated with the ElevenLabs account

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function for the 'list_phone_numbers' MCP tool. It fetches the list of phone numbers using the ElevenLabs client API, formats the information including phone number, ID, provider, label, and assigned agent, and returns it as TextContent. The @mcp.tool decorator registers the tool and defines its description (schema implicitly from function signature).
    @mcp.tool(description="List all phone numbers associated with the ElevenLabs account")
    def list_phone_numbers() -> TextContent:
        """List all phone numbers associated with the ElevenLabs account.
    
        Returns:
            TextContent containing formatted information about the phone numbers
        """
        response = client.conversational_ai.phone_numbers.list()
    
        if not response:
            return TextContent(type="text", text="No phone numbers found.")
    
        phone_info = []
        for phone in response:
            assigned_agent = "None"
            if phone.assigned_agent:
                assigned_agent = f"{phone.assigned_agent.agent_name} (ID: {phone.assigned_agent.agent_id})"
    
            phone_info.append(
                f"Phone Number: {phone.phone_number}\n"
                f"ID: {phone.phone_number_id}\n"
                f"Provider: {phone.provider}\n"
                f"Label: {phone.label}\n"
                f"Assigned Agent: {assigned_agent}"
            )
    
        formatted_info = "\n\n".join(phone_info)
        return TextContent(type="text", text=f"Phone Numbers:\n\n{formatted_info}")
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose any behavioral traits like pagination, rate limits, authentication needs, or what 'associated with the ElevenLabs account' entails (e.g., owned vs. available). This is a significant gap for a tool with no annotation coverage.

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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse for an agent.

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?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on behavior, output format, or integration with siblings. Without annotations or output schema, more detail would improve completeness, but it's not entirely incomplete for a basic list tool.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, but it could have mentioned implicit constraints like authentication. Baseline is 4 for zero parameters, as it doesn't mislead or omit required info.

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 action ('List all') and resource ('phone numbers associated with the ElevenLabs account'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_agents' or 'list_conversations' beyond the resource type, which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives, such as whether it's for account management, billing, or voice-related tasks. With many sibling tools available, this lack of context leaves the agent without clear usage criteria.

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/projectservan8n/elevenlabs-mcp'

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