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ha-automation-mcp

ha-automation-mcp

by aderik
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

call_service

Invoke Home Assistant services via native REST API to control entities, set attributes, or trigger automations without editing YAML.

Instructions

Call any Home Assistant service via the native REST API.

Example: domain='light', service='turn_on', data={'entity_id': 'light.kitchen', 'brightness': 200}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>",
      "service": "<service>"
    },
    "name": "call_service"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataNo
domainYes
serviceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.5/5.0
Behavior1/5

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

There are no annotations provided, so the description must carry the full behavioral burden. It does not disclose any behavioral traits beyond the basic action: no mention of side effects, required permissions, rate limits, error handling, or what happens on success/failure. For a generic service-calling tool that could trigger arbitrary actions (lights, locks, etc.), this is a significant gap.

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 brief and front-loaded with the core action, followed by an example. It is efficient and contains no extraneous information. The example is useful and concise.

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

Completeness2/5

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

Given the complexity (a generic tool that can call any service) and the lack of annotations, output schema, and parameter documentation, the description is incomplete. It should explain more about the expected format of 'data', what domains/services are available, and any safety considerations. The example helps but doesn't compensate for the missing guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning none of the parameters are documented in the schema. The description includes an example that shows the format of domain, service, and data, which adds some meaning. However, it doesn't explain that 'data' should contain service-specific parameters or that it's optional, leaving ambiguity for the agent.

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 ('Call any Home Assistant service via the native REST API'), which is a specific verb and resource. It distinguishes itself from siblings like list_automations or get_state, which are more specific. However, it doesn't explicitly mention what makes it different from other generic tools, but the purpose is understandable.

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. It does not state when it should be used, what prerequisites exist, or what alternatives exist. The example shows how to invoke it but not when.

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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