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4tal

MCP Google Contacts Server

by 4tal

update_contact_advanced

Update existing Google Contacts with comprehensive field support including multiple emails, phone numbers, addresses, and other contact details.

Instructions

Update an existing contact with full field support including multiple emails, phones, addresses, etc.

    Args:
        resource_name: Contact resource name (people/*)
        contact_data: Dictionary containing updated contact information with full field support
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resource_nameYes
contact_dataYes

Implementation Reference

  • The core handler function for the 'update_contact_advanced' tool. Decorated with @mcp.tool() for registration. Initializes the Google Contacts service, calls service.update_contact with the provided parameters, formats the result, and handles errors.
    @mcp.tool()
    async def update_contact_advanced(resource_name: str, contact_data: Dict[str, Any]) -> str:
        """Update an existing contact with full field support including multiple emails, phones, addresses, etc.
    
        Args:
            resource_name: Contact resource name (people/*)
            contact_data: Dictionary containing updated contact information with full field support
        """
        service = init_service()
        if not service:
            return "Error: Google Contacts service is not available. Please check your credentials."
    
        try:
            contact = service.update_contact(resource_name, contact_data)
            return f"Advanced contact updated successfully!\n\n{format_contact(contact)}"
        except Exception as e:
            return f"Error: Failed to update advanced contact - {str(e)}"
  • src/tools.py:64-73 (registration)
    Top-level registration function that invokes register_contact_tools (where update_contact_advanced is defined and registered via nested @mcp.tool()).
    def register_tools(mcp: FastMCP) -> None:
        """Register all Google Contacts tools with the MCP server.
    
        Args:
            mcp: FastMCP server instance
        """
        register_contact_tools(mcp)
        register_directory_tools(mcp)
        register_contact_group_tools(mcp)
  • src/main.py:74-75 (registration)
    In main.py, register_tools is called on the FastMCP instance to register all tools, including 'update_contact_advanced'.
    register_tools(mcp)
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it's an update operation. It doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, error conditions, or what happens to unspecified fields. For a mutation tool with zero annotation coverage, this is inadequate.

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 efficiently structured with a clear purpose statement followed by parameter documentation. However, the parameter section uses informal formatting ('Args:') and could be more integrated. Overall, it's appropriately sized with minimal waste.

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?

For a mutation tool with 2 parameters (including a complex nested object), 0% schema coverage, no annotations, and no output schema, the description is insufficient. It lacks critical information about behavior, parameter details, error handling, and comparison to siblings, leaving the agent poorly equipped to use it correctly.

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 description coverage is 0%, so the schema provides no parameter documentation. The description adds basic semantics for both parameters ('Contact resource name' and 'Dictionary containing updated contact information'), but doesn't explain format, constraints, or examples for 'contact_data' despite its complexity. It partially compensates but leaves significant gaps.

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 verb ('Update') and resource ('existing contact') with specific scope ('full field support including multiple emails, phones, addresses, etc.'). It distinguishes from the simpler 'update_contact' sibling by emphasizing advanced capabilities, though it doesn't explicitly name the sibling alternative.

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 the simpler 'update_contact' sibling or other contact-related tools. It mentions 'full field support' but doesn't clarify prerequisites, constraints, or alternative scenarios.

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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