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search_methods

Search Meraki API methods by entering a keyword like 'admin', 'firewall', or 'ssid' to find relevant endpoints.

Instructions

Search for Meraki API methods by keyword

Args: keyword: Search term (e.g., 'admin', 'firewall', 'ssid', 'event')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler for search_methods tool. Searches _METHOD_INDEX (grouped by SDK section) for methods matching the keyword (case-insensitive). Returns a JSON string with matching results grouped by section and total match count.
    @mcp.tool()
    async def search_methods(keyword: str) -> str:
        """
        Search for Meraki API methods by keyword
    
        Args:
            keyword: Search term (e.g., 'admin', 'firewall', 'ssid', 'event')
        """
        keyword_lower = keyword.lower()
        results = {
            section: [m for m in methods if keyword_lower in m.lower()]
            for section, methods in _METHOD_INDEX.items()
        }
        results = {k: v for k, v in results.items() if v}
    
        return json.dumps({
            "keyword": keyword,
            "results": results,
            "total_matches": sum(len(v) for v in results.values()),
            "usage": "Use call_meraki_api(section='...', method='...', parameters='{...}')"
        }, indent=2)
  • Input schema: keyword (str) is the only parameter. No return type schema beyond str.
    @mcp.tool()
    async def search_methods(keyword: str) -> str:
        """
        Search for Meraki API methods by keyword
    
        Args:
            keyword: Search term (e.g., 'admin', 'firewall', 'ssid', 'event')
        """
  • Registered as an MCP tool via @mcp.tool() decorator on the FastMCP server instance named 'mcp'.
    @mcp.tool()
  • Helper function _build_method_index() builds the _METHOD_INDEX dict (grouped by SDK section) that search_methods queries against. It introspects the meraki dashboard object to discover all callable methods per section.
    def _build_method_index() -> Dict:
        """Build a complete index of all callable SDK methods, grouped by section."""
        index = {}
        for section_name in SDK_SECTIONS:
            if not hasattr(dashboard, section_name):
                continue
            section_obj = getattr(dashboard, section_name)
            methods = sorted(
                m for m in dir(section_obj)
                if not m.startswith('_') and callable(getattr(section_obj, m))
            )
            if methods:
                index[section_name] = methods
        return index
    
    _METHOD_INDEX = _build_method_index()
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. The description only states the basic purpose and gives keyword examples. It does not disclose traits like case sensitivity, behavior on empty or no-match keywords, pagination, or response format. For a search tool, this is insufficient.

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 very concise, consisting of only two short sentences and an example. It front-loads the purpose and immediately provides usage context via examples. No extraneous information.

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?

The tool is simple (one required parameter) and has an output schema, so the description need not detail return values. However, it lacks completeness in terms of specifying behavior on edge cases (e.g., no matches, case sensitivity). For a minimal search tool, it is adequate but not comprehensive.

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?

The input schema has 0% description coverage, meaning the JSON schema provides no explanation for the 'keyword' parameter. The description partially compensates by providing concrete examples ('admin', 'firewall', 'ssid', 'event'), adding meaning beyond 'string'. However, it does not specify expected format or constraints.

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 tool searches for Meraki API methods by keyword, using a specific verb ('Search') and resource ('Meraki API methods'). It distinguishes from siblings like 'get_method_info' (retrieves details of a specific method) and 'list_all_methods' (lists all methods).

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

Usage Guidelines4/5

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

The description provides a clear context for using the tool to search by keyword, with examples of valid keywords. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'get_method_info' for detailed info on a single method) or when not to use it. This is implicit in the sibling names, but not explicit.

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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