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RyoJerryYu

MCP Server Memos

by RyoJerryYu

create_memo

Create and store memos with customizable visibility settings to organize thoughts and information in the MCP Server Memos system.

Instructions

Create a new memo

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe content of the memo.
visibilityNoThe visibility of the memo.PRIVATE

Implementation Reference

  • The primary handler for the 'create_memo' MCP tool. It validates the input arguments using CreateMemoRequest, constructs a protobuf CreateMemoRequest, calls the underlying memo_service gRPC stub to create the memo, and returns a TextContent response with the created memo's name.
    async def create_memo(self, args: dict) -> list[types.TextContent]:
        try:
            params = CreateMemoRequest.model_validate(args)
        except Exception as e:
            raise McpError(types.INVALID_PARAMS, str(e))
    
        req = memos_api_v1.CreateMemoRequest(
            content=params.content,
            visibility=params.visibility.to_proto(),
        )
        res = await self.memo_service.create_memo(create_memo_request=req)
        content = f"Memo created: {res.name}"
        return [types.TextContent(type="text", text=content)]
  • Pydantic BaseModel defining the input schema for the create_memo tool, including content (string) and visibility (enum: PUBLIC, PROTECTED, PRIVATE).
    class CreateMemoRequest(BaseModel):
        """Request to create memo"""
    
        content: Annotated[
            str,
            Field(
                description="""The content of the memo.""",
            ),
        ]
        visibility: Annotated[
            Visibility,
            Field(default=Visibility.PRIVATE, description="""The visibility of the memo."""),
        ]
  • Registration of the 'create_memo' tool in the MCP server's list_tools() handler, specifying name, description, and input schema.
        name=MemosTools.CREATE_MEMO,
        description="Create a new memo",
        inputSchema=CreateMemoRequest.model_json_schema(),
    ),
  • Dispatch logic in the MCP server's call_tool() handler that routes calls to the create_memo handler when the tool name matches.
    elif name == MemosTools.CREATE_MEMO:
        return await tool_adapter.create_memo(args)
  • Enum defining the tool names, including CREATE_MEMO = "create_memo", used throughout for registration and dispatching.
    class MemosTools(str, Enum):
        LIST_MEMO_TAGS = "list_memo_tags"
        SEARCH_MEMO = "search_memo"
        CREATE_MEMO = "create_memo"
        GET_MEMO = "get_memo"
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 'create a new memo', implying a write operation, but doesn't cover permissions, side effects, error handling, or response format. This is a significant gap for a mutation tool with zero annotation coverage.

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 with the core action and resource, making it easy to parse quickly. No extraneous details or redundancy are present.

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 complexity of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a memo is, how it's stored, what happens on success/failure, or any behavioral traits. This leaves critical gaps for an agent to invoke the tool effectively.

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 already documents both parameters ('content' and 'visibility') with descriptions and defaults. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action ('create') and resource ('memo'), making the basic purpose clear. However, it's vague about what a 'memo' entails and doesn't differentiate from siblings like 'get_memo' or 'search_memo' beyond the verb. It's functional but lacks specificity about the memo's nature or scope.

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 like 'search_memo' or 'list_memo_tags'. The description implies it's for creating new memos, but there's no mention of prerequisites, constraints, or typical use cases, leaving the agent to infer usage from context alone.

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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