Skip to main content
Glama
ssinha3

Time MCP Server

by ssinha3

convert_time

Convert time between timezones using IANA timezone names. Input source and target timezones (e.g., 'America/New_York', 'Asia/Tokyo') with time in 24-hour format (HH:MM) to get accurate conversions.

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.
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.
timeYesTime to convert in 24-hour format (HH:MM)

Implementation Reference

  • The main handler function in TimeServer class that performs timezone conversion from source_tz time_str to target_tz, outputs TimeConversionResult with source/target times and difference.
    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"),
                is_dst=bool(source_time.dst()),
            ),
            target=TimeResult(
                timezone=target_tz,
                datetime=target_time.isoformat(timespec="seconds"),
                is_dst=bool(target_time.dst()),
            ),
            time_difference=time_diff_str,
        )
  • Tool registration in list_tools(), defining name, description, and inputSchema for 'convert_time' tool.
    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 call_tool() 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"],
        )
    case _:
  • Pydantic model for the output structure of convert_time tool.
    class TimeConversionResult(BaseModel):
        source: TimeResult
        target: TimeResult
        time_difference: str
  • Pydantic model used in TimeConversionResult for source and target time details.
    class TimeResult(BaseModel):
        timezone: str
        datetime: str
        is_dst: bool
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 the tool's function but doesn't disclose behavioral traits like error handling, format validation, or what happens with invalid inputs. For a tool with no annotations, this leaves significant gaps in understanding its operation.

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 with zero waste. It's front-loaded and appropriately sized for the tool's complexity, making it easy to understand quickly without unnecessary elaboration.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, error cases, or output format, which are important for a conversion tool without structured output documentation.

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%, so the schema fully documents all parameters. The description adds no additional meaning beyond what's in the schema, such as examples or edge cases. Baseline 3 is appropriate as the schema handles parameter documentation effectively.

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. It distinguishes from the sibling 'get_current_time' by focusing on conversion rather than retrieval, though it doesn't explicitly mention this 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, constraints, or compare it with 'get_current_time'. Usage is implied by the purpose but lacks explicit context or exclusions.

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

Related 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/ssinha3/mcp-time-server'

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