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Encoding MCP Server

get_system_info

Retrieve system information about available libraries and supported encodings to ensure compatibility with Windows build environments and prevent character encoding issues.

Instructions

Check Encoding MCP system information. Shows available libraries and supported encodings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function that gathers and formats system information about available encoding detection methods, recommended libraries, and supported encodings.
    def get_system_info() -> str:
        """
        Return system information.
        """
        detection_methods = get_available_detection_methods()
        supported_encodings = list_supported_encodings()
        
        info_text = "šŸ”§ Encoding MCP v2.0.1 System Information\n\n"
        
        # Detection methods
        info_text += "šŸ“Š Available encoding detection methods:\n"
        for method, available in detection_methods.items():
            status = "āœ…" if available else "āŒ"
            info_text += f"  {status} {method}\n"
        
        info_text += f"\nšŸ“š Recommended libraries:\n{get_recommended_libraries()}\n\n"
        
        # Supported encodings
        info_text += "šŸŽÆ Supported encodings:\n"
        for encoding, info in supported_encodings.items():
            windows_icon = "🪟" if info['windows_friendly'] else "🐧"
            info_text += f"  {windows_icon} {encoding}: {info['name']}\n"
        
        return info_text
  • The input schema definition for the get_system_info tool, which takes no parameters.
    Tool(
        name="get_system_info",
        description="Check Encoding MCP system information. Shows available libraries and supported encodings.",
        inputSchema={
            "type": "object",
            "properties": {},
            "required": []
        }
    )
  • The registration and dispatch logic in the @app.call_tool() handler that calls the get_system_info function and formats the response as MCP TextContent.
    elif name == "get_system_info":
        system_info = get_system_info()
        
        return [
            types.TextContent(
                type="text",
                text=system_info
            )
        ]
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what information the tool provides but doesn't describe important behavioral aspects like whether this is a read-only operation, whether it requires authentication, what format the information is returned in, or any limitations. The description is purely functional without 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 appropriately concise with two sentences that directly state the tool's purpose and what information it provides. It's front-loaded with the main purpose and follows with specific details. There's no wasted language or unnecessary elaboration for this simple informational tool.

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 this is a simple informational tool with 0 parameters, no annotations, and no output schema, the description provides adequate but minimal coverage. It tells what the tool does but doesn't address format of returned information or any behavioral constraints. For a zero-parameter read operation, this is minimally viable but lacks completeness about what the agent should expect in return.

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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't mention parameters since none exist, which is correct for a zero-parameter tool. Baseline for this situation would be 4 since the description doesn't need to compensate for any parameter documentation 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 tool's purpose: 'Check Encoding MCP system information' with specific details about what information is shown ('available libraries and supported encodings'). It uses a clear verb ('Check') and identifies the resource ('system information'), though it doesn't explicitly differentiate from sibling tools like 'detect_file_encoding' which serves a different purpose.

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. While it's clear this tool shows system information rather than performing file operations like the sibling tools, there's no explicit mention of when this tool should be selected over other options or what context would make it appropriate.

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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