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asaficontact

Time MCP Server

by asaficontact

convert_time

Convert time between different timezones using IANA timezone names. Input a time and source timezone to get the equivalent time in a target timezone.

Instructions

Convert time between timezones

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_timezoneYesSource IANA timezone name (e.g., 'America/New_York', 'Europe/London'). Use 'Etc/UTC' as local timezone if no source timezone provided by the user.
timeYesTime to convert in 24-hour format (HH:MM)
target_timezoneYesTarget IANA timezone name (e.g., 'Asia/Tokyo', 'America/San_Francisco'). Use 'Etc/UTC' as local timezone if no target timezone provided by the user.

Implementation Reference

  • The primary handler method for the 'convert_time' tool in the TimeServer class. It validates the input time format, converts the time from the source timezone to the target timezone using datetime operations, calculates the time difference, and constructs a TimeConversionResult object.
    def convert_time(
        self, source_tz: str, time_str: str, target_tz: str
    ) -> TimeConversionResult:
        """Convert time between timezones"""
        source_timezone = get_zoneinfo(source_tz)
        target_timezone = get_zoneinfo(target_tz)
    
        try:
            parsed_time = datetime.strptime(time_str, "%H:%M").time()
        except ValueError:
            raise ValueError("Invalid time format. Expected HH:MM [24-hour format]")
    
        now = datetime.now(source_timezone)
        source_time = datetime(
            now.year,
            now.month,
            now.day,
            parsed_time.hour,
            parsed_time.minute,
            tzinfo=source_timezone,
        )
    
        target_time = source_time.astimezone(target_timezone)
        source_offset = source_time.utcoffset() or timedelta()
        target_offset = target_time.utcoffset() or timedelta()
        hours_difference = (target_offset - source_offset).total_seconds() / 3600
    
        if hours_difference.is_integer():
            time_diff_str = f"{hours_difference:+.1f}h"
        else:
            # For fractional hours like Nepal's UTC+5:45
            time_diff_str = f"{hours_difference:+.2f}".rstrip("0").rstrip(".") + "h"
    
        return TimeConversionResult(
            source=TimeResult(
                timezone=source_tz,
                datetime=source_time.isoformat(timespec="seconds"),
                day_of_week=source_time.strftime("%A"),
                is_dst=bool(source_time.dst()),
            ),
            target=TimeResult(
                timezone=target_tz,
                datetime=target_time.isoformat(timespec="seconds"),
                day_of_week=target_time.strftime("%A"),
                is_dst=bool(target_time.dst()),
            ),
            time_difference=time_diff_str,
        )
  • Pydantic model defining the output structure for the 'convert_time' tool response, including source and target time details and the time difference.
    class TimeConversionResult(BaseModel):
        source: TimeResult
        target: TimeResult
        time_difference: str
  • Pydantic model used within TimeConversionResult for representing time information in a specific timezone.
    class TimeResult(BaseModel):
        timezone: str
        datetime: str
        day_of_week: str
        is_dst: bool
  • Registration of the 'convert_time' tool in the MCP server's list_tools() method, defining the tool name, description, and input schema.
    Tool(
        name=TimeTools.CONVERT_TIME.value,
        description="Convert time between timezones",
        inputSchema={
            "type": "object",
            "properties": {
                "source_timezone": {
                    "type": "string",
                    "description": f"Source IANA timezone name (e.g., 'America/New_York', 'Europe/London'). Use '{local_tz}' as local timezone if no source timezone provided by the user.",
                },
                "time": {
                    "type": "string",
                    "description": "Time to convert in 24-hour format (HH:MM)",
                },
                "target_timezone": {
                    "type": "string",
                    "description": f"Target IANA timezone name (e.g., 'Asia/Tokyo', 'America/San_Francisco'). Use '{local_tz}' as local timezone if no target timezone provided by the user.",
                },
            },
            "required": ["source_timezone", "time", "target_timezone"],
        },
    ),
  • Dispatch logic in the MCP server's call_tool() method that validates arguments and invokes the 'convert_time' handler.
    case TimeTools.CONVERT_TIME.value:
        if not all(
            k in arguments
            for k in ["source_timezone", "time", "target_timezone"]
        ):
            raise ValueError("Missing required arguments")
    
        result = time_server.convert_time(
            arguments["source_timezone"],
            arguments["time"],
            arguments["target_timezone"],
        )
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool's function but does not cover critical aspects like error handling (e.g., invalid timezone inputs), format constraints beyond the schema, or response behavior (e.g., output format). This leaves significant gaps in understanding how the tool behaves in practice.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick comprehension.

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 tool's complexity (time conversion with three required parameters) and lack of annotations and output schema, the description is insufficient. It does not explain return values, error conditions, or behavioral nuances, leaving the agent with incomplete information to invoke the tool effectively in varied contexts.

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 100%, with all parameters well-documented in the input schema. The description adds no additional meaning beyond the schema, such as examples or edge cases, but since the schema provides comprehensive details, the baseline score of 3 is appropriate as the description does not detract from parameter understanding.

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 'Convert time between timezones' clearly states the verb ('convert') and resource ('time'), specifying the operation's scope. However, it does not explicitly differentiate from the sibling tool 'get_current_time', which likely retrieves current time without conversion, leaving some ambiguity in sibling distinction.

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 the sibling 'get_current_time'. It lacks context on prerequisites, exclusions, or specific scenarios for application, offering only a basic functional statement without usage instructions.

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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