Skip to main content
Glama

list_all_methods

List all available Meraki API methods. Optionally filter by section such as organizations, networks, wireless, switch, or appliance.

Instructions

List all available Meraki API methods

Args: section: Optional section filter (organizations, networks, wireless, switch, appliance, etc.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'list_all_methods' tool. Decorated with @mcp.tool(), it lists all available Meraki API methods, optionally filtered by section. Returns JSON with sections, total method count, and usage instructions.
    @mcp.tool()
    async def list_all_methods(section: str = None) -> str:
        """
        List all available Meraki API methods
    
        Args:
            section: Optional section filter (organizations, networks, wireless, switch, appliance, etc.)
        """
        if section:
            if section not in _METHOD_INDEX:
                return json.dumps({
                    "error": f"Section '{section}' not found",
                    "available_sections": list(_METHOD_INDEX.keys())
                }, indent=2)
            sections_to_show = {section: _METHOD_INDEX[section]}
        else:
            sections_to_show = _METHOD_INDEX
    
        return json.dumps({
            "sections": sections_to_show,
            "total_methods": sum(len(v) for v in sections_to_show.values()),
            "usage": "Use call_meraki_api(section='...', method='...', parameters='{...}') to call any method"
        }, indent=2)
  • The helper function _build_method_index() builds a complete index of all callable SDK methods grouped by section. It iterates over SDK_SECTIONS, introspects each section object via dir(), and collects callable methods. The result is stored in _METHOD_INDEX used by list_all_methods.
    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()
  • Registration of the 'list_all_methods' tool via the @mcp.tool() decorator on the handler function.
    @mcp.tool()
  • Input schema for the tool: accepts an optional 'section' parameter of type str. Output is a JSON string containing the method listing.
    async def list_all_methods(section: str = None) -> str:
  • SDK_SECTIONS constant defines the list of Meraki API sections used by _build_method_index() to scan for available methods. These section names are the valid values for the 'section' parameter of list_all_methods.
    SDK_SECTIONS = [
        'organizations',
        'networks',
        'devices',
        'wireless',
        'switch',
        'appliance',
        'camera',
        'cellularGateway',
        'sensor',
        'sm',
        'insight',
        'licensing',
        'administered'
    ]
Behavior3/5

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

No annotations provided, but the description is adequate for a simple read operation. However, it does not detail potential side effects or authorization requirements.

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?

Very concise: one line for the main description and one line for the parameter doc. No waste.

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

Completeness5/5

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

Given the tool's simplicity and presence of an output schema, the description sufficiently covers purpose and parameter behavior.

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?

With 0% schema coverage, the description adds meaning by explaining the section parameter as an optional filter with examples, compensating for the schema gap.

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 'List all available Meraki API methods' with a specific verb and resource. It distinguishes from siblings like get_method_info and search_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 implies usage via the section filter but lacks explicit when-not or alternative tool guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/CiscoDevNet/meraki-magic-mcp-community'

If you have feedback or need assistance with the MCP directory API, please join our Discord server