これは、Home Assistant との統合ツールを提供し、AI アシスタントがスマート ホーム デバイスと対話できるようにする MCP (Model Context Protocol) サーバーです。
Smithery経由で Claude Desktop の Home Assistant Integration を自動的にインストールするには:
npx -y @smithery/cli install @guilhermelirio/homeassistant-mpc --client claude依存関係をインストールします:
npm install環境変数を設定します。
ホームアシスタントから長期アクセストークンを取得する
プロジェクト ルートの.envファイルで環境変数を設定します。
HOME_ASSISTANT_URL=http://your-home-assistant:8123
HOME_ASSISTANT_TOKEN=your_token_hereRelated MCP server: Home Assistant MCP Server
npm start開発の場合:
npm run devhomeassistant_api : Home Assistant APIがオンラインかどうかを確認します
パラメータ: なし
例: homeassistant_api()
homeassistant_get_state : Home Assistantエンティティの現在の状態を取得します
パラメータ: entity_id (エンティティID)
例: homeassistant_get_state("light.living_room")
homeassistant_call_service : Home Assistantエンティティのサービスを呼び出す
パラメータ:
entity_id (エンティティID)
domain （サービスドメイン）
service （呼び出すサービス）
例: homeassistant_call_service("light.living_room", "light", "turn_on")
このプロジェクトでは、TypeScript と MCP SDK ライブラリを使用して、Claude、GPT などの言語モデルからアクセスできるツールを作成します。
新しいツールを追加するには:
src/tools/[category]にモジュールを作成する
既存のパターンに従ってツールを実装する
src/index.tsにモジュールを登録する
貢献を歓迎します！お気軽に問題を報告したり、プルリクエストを送信してください。
このプロジェクトは MIT ライセンスに基づいてライセンスされています - 詳細については LICENSE ファイルを参照してください。
Verify if the Home Assistant API is online
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool verifies if the API is online, implying a read-only check, but doesn't specify what 'online' means (e.g., connectivity, authentication status), potential side effects, or response format. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose, making it easy to parse and understand quickly. Every part of the sentence earns its place by directly contributing to the tool's intent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (zero parameters, no output schema), the description is minimal but adequate for basic understanding. However, without annotations or an output schema, it lacks details on behavioral traits (e.g., what 'verify' entails, error handling) and return values, making it incomplete for reliable agent use in more complex scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100%, so the schema fully documents the lack of inputs. The description doesn't need to add parameter information, and it appropriately doesn't mention any. A baseline of 4 is applied for zero-parameter tools with high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('verify') and resource ('Home Assistant API'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like homeassistant_get_state, which might also check system status, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like homeassistant_get_state or homeassistant_call_service. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage based solely on the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Call a service of a Home Assistant entity
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The domain of the service | |
| entity_id | Yes | The entity ID of the Home Assistant entity | |
| service | Yes | The service to call |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool calls a service but doesn't explain what that entails—whether it's a read, write, or destructive operation, what permissions are needed, or how errors are handled. This leaves significant gaps for a tool that likely performs mutations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of calling a service (likely a mutation), the lack of annotations and output schema, and the description's minimal detail, this is incomplete. The agent lacks crucial information about behavior, return values, and error handling, making it inadequate for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all three parameters (domain, entity_id, service). The description adds no additional meaning beyond what the schema provides, such as examples or contextual usage, but meets the baseline for adequate coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('call a service') and the target ('Home Assistant entity'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its siblings (homeassistant_api and homeassistant_get_state), which would require explicit differentiation to earn a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like homeassistant_api or homeassistant_get_state. There's no mention of prerequisites, use cases, or exclusions, leaving the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the state of a Home Assistant entity
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes | The entity ID of the Home Assistant entity |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Get the state') but doesn't describe what the state includes (e.g., attributes, last_changed), error conditions (e.g., invalid entity_id), authentication requirements, or rate limits. This leaves significant gaps for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste. It's appropriately sized for a simple tool and front-loads the core purpose without unnecessary elaboration. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain what the state return value includes (e.g., JSON structure with attributes), error handling, or how it differs from sibling tools. For a state retrieval tool, this leaves the agent guessing about behavioral outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'entity_id' parameter fully documented. The description adds no additional meaning beyond what the schema provides (e.g., no examples of entity_id format or constraints). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('state of a Home Assistant entity'). It distinguishes from siblings like 'homeassistant_call_service' by focusing on state retrieval rather than service invocation. However, it doesn't explicitly differentiate from 'homeassistant_api' which might be more generic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. There's no mention of prerequisites, when to choose this over 'homeassistant_api' for state retrieval, or any context about entity availability. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0homeassistant_apihomeassistant_call_servicehomeassistant_get_stateScored across 3 tools
Each tool has a clearly distinct purpose: one checks API status, one calls services, and one retrieves entity states. There is no overlap in functionality, making it easy for an agent to select the correct tool without confusion.
All tool names follow a consistent snake_case pattern with a 'homeassistant_' prefix and descriptive verb_noun combinations (api, call_service, get_state). This uniformity enhances readability and predictability.
With only 3 tools, the set feels thin for a Home Assistant integration, which typically involves more operations like listing entities, setting states, or handling events. While the tools cover basic needs, the scope could be expanded for better coverage.
The tools provide core functionality (API check, service calls, state retrieval) but lack operations like listing entities, updating states, or handling events. This creates minor gaps that agents might need to work around, though basic workflows are supported.
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