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updateMock

Updates a mock server's name, environment, privacy, or default response using its ID.

Instructions

Updates a mock server (name, environment, privacy, default response).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mockIdYesMock server ID
mockNoMock server updates

Implementation Reference

  • The UpdateMockTool class - the handler that executes the 'updateMock' tool logic. It extends ToolHandler, calls the Postman API PUT /mocks/{mockId} to update a mock server's name, environment, privacy, default response, etc.
    class UpdateMockTool(ToolHandler):
        """Update mock server"""
        
        def __init__(self):
            super().__init__("updateMock")
        
        def get_tool_description(self) -> Tool:
            return Tool(
                name=self.name,
                description="Updates a mock server (name, environment, privacy, default response).",
                inputSchema={
                    "type": "object",
                    "properties": {
                        "mockId": {
                            "type": "string",
                            "description": "Mock server ID"
                        },
                        "mock": {
                            "type": "object",
                            "description": "Mock server updates"
                        }
                    },
                    "required": ["mockId"]
                },
            )
        
        async def run_tool(self, args: dict) -> list[TextContent]:
            mock_id = args["mockId"]
            body = {"mock": args.get("mock", {})}
            
            result = await postman_api_call("PUT", f"/mocks/{mock_id}", body=body)
            return [TextContent(type="text", text=json.dumps(result, indent=2))]
  • Input schema definition for the updateMock tool, defining input properties: mockId (string, required) and mock (object, optional) for mock server updates.
    def get_tool_description(self) -> Tool:
        return Tool(
            name=self.name,
            description="Updates a mock server (name, environment, privacy, default response).",
            inputSchema={
                "type": "object",
                "properties": {
                    "mockId": {
                        "type": "string",
                        "description": "Mock server ID"
                    },
                    "mock": {
                        "type": "object",
                        "description": "Mock server updates"
                    }
                },
                "required": ["mockId"]
            },
        )
  • Registration of UpdateMockTool() in the register_all_tools() function. This is where the tool is instantiated and included in the list of all 41 registered tools.
    UpdateMockTool(),
    PublishMockTool(),
  • The ToolHandler abstract base class that UpdateMockTool inherits from, providing the abstract interface (get_tool_description, run_tool) for all tool handlers.
    class ToolHandler(ABC):
        """Base class for all Postman tool handlers"""
        
        def __init__(self, name: str):
            self.name = name
        
        @abstractmethod
        def get_tool_description(self) -> Tool:
            """Return the MCP Tool description for this handler"""
            pass
        
        @abstractmethod
        async def run_tool(self, arguments: dict) -> list[TextContent | ImageContent | EmbeddedResource]:
            """Execute the tool with the given arguments"""
            pass
Behavior2/5

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

No annotations provided, so the description must disclose behavioral traits. It only says 'updates', implying mutation, but lacks details like permissions required, idempotency, side effects, or whether partial updates are supported.

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?

A single sentence that is direct and contains no redundant information. Every word earns its place.

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 no output schema and a nested object parameter, the description could be more complete. It does not mention return value or confirm successful update. However, it covers the core update functionality adequately for a minimum viable description.

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?

Schema coverage is 100% (both parameters described), so baseline is 3. The description adds value by listing updatable fields (name, environment, privacy, default response) within the mock object, though it doesn't fully describe the nested structure.

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

Purpose5/5

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

The description clearly states the verb 'Updates' and the resource 'mock server', listing specific fields (name, environment, privacy, default response). It distinguishes from sibling tools like createMock, publishMock, and getMock.

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 on when to use this tool vs alternatives. With many sibling tools (e.g., createMock, publishMock), the description should provide context such as prerequisites or when to update vs create.

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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