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search_apis

Discover available actions and tools within the Jentic MCP server by describing your intent. Find functionalities like managing servers or sending messages quickly.

Instructions

Search for available actions or information based on what the user wants to do (e.g., 'find Discord servers', 'send a message'). Use this first to understand what's possible.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capability_descriptionYesNatural language description of the action needed (e.g., 'send emails', 'weather forecasting', 'natural language processing')
keywordsNoOptional list of specific keywords to help narrow down the search
max_resultsNoMaximum number of actions to return

Implementation Reference

  • Core implementation of the search_apis tool handler in MCPAdapter. Constructs SearchRequest and calls Jentic SDK search method.
    async def search_api_capabilities(self, request: dict[str, Any]) -> dict[str, Any]:
        """MCP endpoint for searching API capabilities.
    
        Args:
            request: MCP tool request parameters.
    
        Returns:
            MCP tool response.
        """
        # Build SearchRequest using the new SDK
        search_request = SearchRequest(
            query=request.get("capability_description") or request.get("query", ""),
            keywords=request.get("keywords"),
            limit=request.get("max_results", 5),
            apis=request.get("api_names"),
        )
    
        search_response = await self.jentic.search(search_request)
    
        # We adopt the unified results list returned by SearchResponse
        response_data = search_response.model_dump(exclude_none=False)
        return {
            "result": {
                "matches": response_data,
                "query": search_request.query,
                "total_matches": search_response.total_count,
            }
        }
  • JSON schema definition for the search_apis tool, defining input parameters and structure.
    SEARCH_API_CAPABILITIES_TOOL = {
        "name": "search_apis",
        "description": "Search for available actions or information based on what the user wants to do (e.g., 'find Discord servers', 'send a message'). Use this first to understand what's possible.",
        "parameters": {
            "type": "object",
            "properties": {
                "capability_description": {
                    "type": "string",
                    "description": "Natural language description of the action needed (e.g., 'send emails', 'weather forecasting', 'natural language processing')",
                },
                "keywords": {
                    "type": "array",
                    "description": "Optional list of specific keywords to help narrow down the search",
                    "items": {"type": "string"},
                },
                "max_results": {
                    "type": "integer",
                    "description": "Maximum number of actions to return",
                    "default": 5,
                },
                "api_names": {
                    "type": "array",
                    "description": "Optional list of API names to restrict results to specific APIs. Use vendor format (e.g., 'google.com') or sub-API format (e.g., 'atlassian.com/jira'). Only results from these APIs will be shown, regardless of search query.",
                    "items": {"type": "string"},
                },
            },
            "required": ["capability_description"],
        },
    }
  • Registration of search_apis handler in the general request handler mapping.
    tool_handlers = {
        "search_apis": mcp_adapter.search_api_capabilities,
        "load_execution_info": mcp_adapter.generate_runtime_config,
        "execute": mcp_adapter.execute,  # Add the execute tool handler
        "submit_feedback": mcp_adapter.submit_feedback
    }
  • Registration of search_apis in stdio transport handlers dictionary.
    self._handlers = {
        "search_apis": self._handle_search_api_capabilities,
        "load_execution_info": self._handle_generate_runtime_from_selection_set,
        "generate_code_sample": self._handle_generate_code_sample,
        "execute": self._handle_execute,  # Add execute handler
        "submit_feedback": self._handle_submit_feedback, # Add submit_feedback handler
    }
  • HTTP endpoint registration for search_apis in HTTP transport, delegating to adapter.
    @self._app.post("/api/search_apis")
    async def search_api_capabilities(request: Request):
        """MCP endpoint for searching API capabilities."""
        data = await request.json()
        result = await self.adapter.search_api_capabilities(data)
        return JSONResponse(result)
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 mentions the tool searches for actions or information but lacks details on behavioral traits such as response format, error handling, rate limits, or authentication needs. For a search tool with zero annotation coverage, this is a significant gap, though it does imply it returns results (e.g., 'to return' in the schema).

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 two sentences that efficiently convey purpose and usage guidelines. Every sentence earns its place by providing essential information without redundancy. It could be slightly more concise by integrating examples more seamlessly, but overall it's well-structured.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers purpose and usage well but lacks behavioral details like return format or error handling. Without annotations or an output schema, the description should do more to compensate, making it minimally viable but incomplete.

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 all three parameters thoroughly. The description does not add any additional meaning beyond what the schema provides, such as explaining how 'capability_description' interacts with 'keywords' or detailing search algorithms. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Search for available actions or information based on what the user wants to do.' It provides a specific verb ('search') and resource ('available actions or information'), with examples like 'find Discord servers' and 'send a message' to illustrate usage. However, it doesn't explicitly distinguish this from sibling tools like 'execute' or 'load_execution_info', 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 Guidelines5/5

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

The description provides explicit guidance on when to use this tool: 'Use this first to understand what's possible.' This clearly indicates it should be employed as an initial step to discover capabilities before invoking other tools, effectively differentiating it from siblings like 'execute' (which likely performs actions) and 'load_execution_info' (which might retrieve details).

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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