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list_saved_apis

Retrieve all saved API configurations from the OpenAPI MCP proxy server to access endpoint details and data models without loading full schemas.

Instructions

List all saved API configurations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function that executes the tool: fetches APIs from config_manager, formats them, and returns as text content.
    async def handle_call(self, arguments: Dict[str, Any]) -> List[TextContent]:
        try:
            apis = self.config_manager.list_apis()
            result = self._format_api_list(apis)
            return self._create_text_response(result)
        except Exception as e:
            return self._create_error_response(e)
  • Defines the tool's input schema (empty object, no parameters) and provides name and description.
    def get_tool_definition(self) -> Tool:
        return Tool(
            name=self.name,
            description=self.description,
            inputSchema={
                "type": "object",
                "properties": {},
                "required": [],
            },
        )
  • Instantiates the ListSavedApisTool and adds it to the registry's tools list.
    RemoveApiTool(self.config_manager),
  • Helper method that formats the list of APIs into a human-readable string.
    def _format_api_list(self, apis: List[Dict[str, str]]) -> str:
        """Format API list for display."""
        if not apis:
            return "No saved APIs found"
    
        result = f"Saved APIs ({len(apis)}):\n\n"
        for api in apis:
            result += f"- {api['name']}: {api['url']}"
            if api.get("description"):
                result += f" - {api['description']}"
            result += "\n"
    
        return result
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 a read operation ('List'), implying it's likely safe and non-destructive, but doesn't specify aspects like pagination, rate limits, or what 'saved' means in terms of permissions or data scope, leaving gaps in transparency.

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, clear sentence with zero waste—it directly states the tool's purpose without fluff or redundancy. It's front-loaded and appropriately sized for a simple list operation, making it highly efficient.

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 simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits like return format or usage context, which could be helpful for an agent despite the low complexity.

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, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any, earning a high score for not introducing unnecessary information.

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 action ('List') and resource ('saved API configurations'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_endpoints' or 'list_models' which also list resources, so it doesn't reach the highest 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 like 'search_endpoints' or 'get_api_info'. It lacks context about prerequisites, such as whether APIs must be saved first, or exclusions, leaving the agent to infer usage from the tool name 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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