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mtct

MCP Journaling Server

by mtct

record_interaction

Save user and assistant messages to create continuous journaling sessions for tracking daily activities and conversation history.

Instructions

Record both the user's message and assistant's response.

Args: user_message: The user's message assistant_message: The assistant's response

Returns: str: Confirmation message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_messageYes
assistant_messageYes

Implementation Reference

  • The main handler function for the 'record_interaction' tool, decorated with @mcp.tool() for registration. It appends both user and assistant messages to the global conversation_log with timestamps and returns a confirmation.
    @mcp.tool()
    async def record_interaction(user_message: str, assistant_message: str) -> str:
        """
        Record both the user's message and assistant's response.
        
        Args:
            user_message: The user's message
            assistant_message: The assistant's response
            
        Returns:
            str: Confirmation message
        """
        # Add user message first
        conversation_log.append({
            "speaker": "user",
            "message": user_message,
            "timestamp": datetime.now().isoformat()
        })
        
        # Then add assistant message
        conversation_log.append({
            "speaker": "assistant",
            "message": assistant_message,
            "timestamp": datetime.now().isoformat()
        })
        
        return "Conversation updated"
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool records messages but doesn't explain where or how (e.g., in a database, log file, or session context), whether it requires permissions, or if it has side effects like overwriting data. This leaves critical behavioral traits unspecified for a mutation tool.

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 sized and front-loaded, with the core purpose stated first in a clear sentence. The Args and Returns sections are structured efficiently, though the 'Returns' part could be more specific than 'Confirmation message.' Overall, it avoids unnecessary verbosity while conveying essential information.

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 complexity (a mutation with 2 parameters), lack of annotations, and no output schema, the description is minimally adequate. It covers the basic action and parameters but misses details like behavioral context, usage relative to siblings, and return value specifics. This leaves gaps that could hinder an agent's understanding in a broader workflow.

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 description adds meaningful semantics beyond the input schema, which has 0% coverage. It explicitly defines 'user_message' as 'The user's message' and 'assistant_message' as 'The assistant's response,' clarifying the purpose of each parameter. Since there are only 2 parameters and the schema lacks descriptions, this compensation is effective, though not exhaustive (e.g., no format constraints).

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: 'Record both the user's message and assistant's response.' It specifies the verb ('record') and resources ('user's message' and 'assistant's response'), making the action explicit. However, it doesn't differentiate from sibling tools like 'generate_session_summary' or 'start_new_session', 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. It doesn't mention sibling tools or contexts where recording interactions is appropriate, such as after a conversation or as part of session management. Without such guidance, agents may struggle to select this tool correctly in relation to others.

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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