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MCP Simulator

by FokkeZB
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search_actions

Describe your goal to discover atomic actions from connected systems, then chain them together to complete your task.

Instructions

STEP 1: Discover available ATOMIC actions by describing what you want to accomplish. Returns a list of atomic actions from connected systems that can be chained together to complete your task.

⚠️ CRITICAL: THE RETURNED ACTIONS ARE NOT TOOLS! They are action names that must be passed to execute_action.

FOR THE ACTION WORKFLOW, USE THESE TWO TOOLS:

  1. search_actions (this tool) - discovers available actions across all connected systems

  2. execute_action - executes a discovered action by name

The actions returned from search_actions are NOT callable as tools. You MUST use execute_action to run them.

ADDITIONAL AVAILABLE TOOLS: 3. get_world_time - get current world time 4. advance_world_time - travel forward in time to see future states

Actions are ATOMIC and must be CHAINED:

  • Each action does ONE thing only (not compound operations)

  • Actions have parameters so you can pass data between them

  • You orchestrate the workflow by calling execute_action multiple times

This server is a universal gateway with connectivity to EVERYTHING: smart home devices, IoT systems, web APIs, cloud services, physical infrastructure, and more. Search broadly and expect comprehensive capabilities across all domains.

EXAMPLE WORKFLOW 1 - Action chaining: User says: "Turn on the lights if it's raining at my location"

  1. Call search_actions with query="Turn on the lights if it's raining at my location"

  2. Receive atomic actions: ["get_current_location", "get_weather_for_location", "turn_on_lights"]

  3. Call execute_action with action_name="get_current_location" → returns "37.7749, -122.4194"

  4. Call execute_action with action_name="get_weather_for_location", parameters={"location": "37.7749, -122.4194"} → returns "raining"

  5. Call execute_action with action_name="turn_on_lights", parameters={"location": "all"} → lights on

EXAMPLE WORKFLOW 2 - Time travel: User says: "Plant tomatoes and check how they're doing in 3 months"

  1. Call search_actions with query="plant tomatoes"

  2. Call execute_action with action_name="plant_seeds", parameters={"type": "tomatoes"} → planted

  3. Call advance_world_time with months=3 → time advances 3 months

  4. Call search_actions with query="check plant status"

  5. Call execute_action with action_name="get_plant_status", parameters={"type": "tomatoes"} → returns growth status after 3 months

NOTE: You have these MCP tools: search_actions, execute_action, get_world_time, advance_world_time. Do NOT try to call action names as if they were tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of actions to return (default: 5)
queryYesDescribe what you want to accomplish in natural language. The gateway will discover relevant actions from all connected systems. Examples: "Turn on the lights if it's raining", "Check the weather and adjust the thermostat", "Lock the front door and turn off all lights"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It transparently explains that returned actions are not callable, must be chained, and require execute_action. It also reveals atomicity and cross-system scope, though it does not address potential side effects, authentication, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is heavily over-specified with repeated warnings, multiple workflow examples, and broad claims about universal connectivity. While it is front-loaded with critical information, much of the content is redundant and could be condensed without losing meaning.

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?

Despite verbosity, the description fully equips an agent to use the tool correctly within the wider action workflow: it explains chaining, names sibling tools, provides two end-to-end examples, and explicitly prohibits calling returned actions as tools. Nothing essential for invocation is missing.

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 baseline is 3. The description reinforces that query is a natural-language description of the desired outcome, but adds little beyond the schema's own examples for the limit parameter. The chaining details are more about execute_action than about search_actions' parameters.

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's purpose: 'Discover available ATOMIC actions by describing what you want to accomplish' and explicitly contrasts it with execute_action. It also clarifies that returned actions are not tools, which distinguishes this tool's output from being directly invocable.

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 workflow guidance: use search_actions to discover actions, then execute_action to run them, and warns not to treat action names as tools. It also names sibling tools (get_world_time, advance_world_time) and shows concrete example workflows, leaving little ambiguity about when to use this tool versus alternatives.

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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