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getEnabledTools

Retrieves information about enabled tools in full and minimal sets. Use this when a requested tool is unavailable.

Instructions

IMPORTANT: Run this first when a requested tool is unavailable. Returns info about enabled tools in full and minimal sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The GetEnabledToolsTool class implementing the 'getEnabledTools' tool. The run_tool method returns a hardcoded JSON response indicating all 41 tools are enabled, with category breakdowns.
    class GetEnabledToolsTool(ToolHandler):
        """Get enabled tools"""
        
        def __init__(self):
            super().__init__("getEnabledTools")
        
        def get_tool_description(self) -> Tool:
            return Tool(
                name=self.name,
                description="IMPORTANT: Run this first when a requested tool is unavailable. Returns info about enabled tools in full and minimal sets.",
                inputSchema={
                    "type": "object",
                    "properties": {},
                },
            )
        
        async def run_tool(self, args: dict) -> list[TextContent]:
            enabled_tools = {
                "message": "All 41 Postman MCP tools are enabled",
                "full_toolset": ["All 41 tools available"],
                "minimal_toolset": ["Core read-only tools available"],
                "total_tools": 41,
                "categories": {
                    "collections": 7,
                    "requests_responses": 3,
                    "environments": 4,
                    "mocks": 5,
                    "specs": 13,
                    "workspaces": 4,
                    "integration": 3,
                    "other": 2
                }
            }
            return [TextContent(type="text", text=json.dumps(enabled_tools, indent=2))]
  • The get_tool_description method defines the input schema (no parameters) and description for the 'getEnabledTools' tool.
    def get_tool_description(self) -> Tool:
        return Tool(
            name=self.name,
            description="IMPORTANT: Run this first when a requested tool is unavailable. Returns info about enabled tools in full and minimal sets.",
            inputSchema={
                "type": "object",
                "properties": {},
            },
        )
  • The register_all_tools() function registers GetEnabledToolsTool() as the second handler in the list of all 41 tools.
    def register_all_tools() -> list[ToolHandler]:
        """Register all Postman tool handlers"""
        return [
            # User Info
            GetAuthenticatedUserTool(),
            GetEnabledToolsTool(),
  • The register_all_postman_tools() function in postman_server.py imports and registers all handlers from postman_tools into the tool_handlers dict.
        request_headers.update(headers)
    
    async with httpx.AsyncClient(timeout=30.0) as client:
        try:
            response = await client.request(
                method=method,
                url=url,
                json=body,
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It implies a read operation but does not explicitly state it is side-effect free or disclose any other behavioral aspects. For a simple informational tool, this is adequate but could be more explicit.

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?

Two sentences, front-loaded with 'IMPORTANT', no wasted words. The key message is immediate and clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description covers the essential purpose and usage context. It mentions 'full and minimal sets' for output, which is sufficient for an agent to understand what to expect, though more detail on the output format could be added.

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?

There are no parameters (schema coverage 100%), so the schema does all the work. The description adds value by mentioning 'full and minimal sets', hinting at the output structure beyond what the schema provides.

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 returns info about enabled tools and should be run first when a requested tool is unavailable. The verb 'return' and resource 'enabled tools' are specific, and it distinguishes from sibling tools that deal with specific resources like collections or environments.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs the agent to run this tool first when a requested tool is unavailable, providing clear when-to-use guidance.

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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