ha-mcp

by qubit999

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: service calls, configuration retrieval, entity queries by area or ID, error logs, history, state listing, area listing, and template rendering. No overlap in functionality.
Naming Consistency5/5
All tools follow a consistent 'ha_{verb}_{noun}' pattern with underscores, using verbs like 'call', 'get', 'list', and 'render'. The prefix 'ha_' identifies the server, and naming is predictable.
Tool Count5/5
With 9 tools covering essential Home Assistant operations (service calls, state queries, configuration, history, error logs, areas, and template rendering), the count is well-scoped for an MCP server without being excessive.
Completeness5/5
The tool set covers core Home Assistant interactions: calling any service, retrieving states, config, history, error logs, and area information. The inclusion of template rendering adds flexibility. No obvious gaps for common tasks.
Average 3.6/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on June 29, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral disclosure. It states it returns state and attributes but omits side effects (likely read-only), auth requirements, error handling, or what happens for missing entities.
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?
One sentence with no wasted words. Includes an example inline. Efficiently conveys the core action and parameter usage.
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?
Adequate for a simple read tool, but with no output schema, it would benefit from mentioning the return format (e.g., JSON object). Sibling tools are provided but not referenced in the description.
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?
With 0% schema description coverage, the description compensates by naming the parameter entity_id and providing an example ('light.kitchen_lights'). However, it does not explain constraints like valid entities or format beyond the example.
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 uses a specific verb 'Get' and resource 'full state and attributes of one entity', with an explicit example of entity_id format. It clearly distinguishes from sibling tools like ha_get_states which presumably return multiple entities.
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?
No guidance on when to use this tool vs alternatives such as ha_get_states or ha_get_history. There are no exclusions or context about when this is the appropriate choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It fails to mention side effects, permission requirements, synchronicity, or error handling. For a tool that triggers real-world actions, 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 concise at two sentences, front-loading the purpose and then providing examples and a usage hint. It is efficient but could be slightly more structured.
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 tool's complexity (general service caller with 4 parameters, no output schema, no annotations), the description is too minimal. It lacks guidance on the domain/service pattern, optionality of entity_id, and the nature of the response, making it incomplete for an agent to use confidently.
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%, so the description must explain parameters. It only addresses the 'data' parameter with a note about extra params. The other parameters (domain, service, entity_id) are not explained, leaving ambiguity despite the examples.
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 'Call any Home Assistant service' and provides specific examples (light.turn_on, climate.set_temperature), which distinguishes it from sibling tools that are all read/get operations.
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 context of use is implied: use when you want to perform an action rather than read. The sibling tools are all query/read functions, so the description's action-oriented purpose provides clear separation. However, it does not explicitly state when not to use it or list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose all behavioral traits. It only states rendering and return of result, omitting error handling (e.g., invalid template), available variables, side effects (likely read-only), and output format. Minimal behavioral disclosure.
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?
The description is concise with two sentences and an immediate example. No superfluous information, efficient and front-loaded.
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?
Given the tool's simplicity (one required string parameter, no output schema), the description is minimally adequate but lacks details on return format, error behavior, and available Jinja2 context. Could be more complete.
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 coverage is 0%, so description must compensate for parameter meaning. The description adds an example but does not explain the 'template' parameter beyond being a string. Lacks details on valid syntax, variable scope, 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 renders a Home Assistant Jinja2 template and returns the result, with a concrete example. This verb+resource combination is unique among siblings, none of which perform template rendering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for template evaluation but does not provide explicit when-to-use or when-not-to-use guidance. There are no alternative tools for template rendering, making the usage context clear but lacking exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states 'Get' implying read-only, but does not disclose idempotency, rate limits, or potential side effects. Minimal disclosure for a simple retrieval tool.
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?
A single, front-loaded sentence with no waste. Every word adds value – verb, resource, format, purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter retrieval tool with no output schema, the description covers the returned content (plain text error log) and usage intent. Could mention if the log is truncated or its typical size, but sufficient for its simplicity.
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?
There are zero parameters and the schema covers 100% trivially. Per guidelines, 0 params baseline is 4, and the description adds no parameter meaning beyond the schema.
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 specifies 'Get the Home Assistant error log (plain text) for troubleshooting' – a clear verb and resource with stated purpose. It distinguishes from siblings like ha_get_config or ha_get_states, but does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for troubleshooting' implies usage context, but there is no explicit when-to-use, when-not-to-use, or alternative guidance. This is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It discloses the time range and default but omits whether the operation is read-only, any side effects, or authentication needs. The read-only nature is implied but not stated.
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?
A single sentence with 12 words, front-loading the purpose and key parameter. No unnecessary 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?
Given no annotations, output schema, or sibling guidance, the description covers the basic purpose but lacks return format details, pagination, or permission context. It is minimally adequate for a simple retrieval tool.
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?
With 0% schema coverage, the description adds meaning by linking 'entity' to entity_id and explaining the 'hours' parameter as the time range with a default. However, it does not explicitly state that entity_id is required or describe expected formats.
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 retrieves state-change history for an entity over a configurable time range. The verb 'Get' and resource 'state-change history' are specific, and the default of 24 hours adds precision. This distinguishes it from siblings like ha_get_entity (current state) and ha_get_states (all current states).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for historical data retrieval but does not explicitly indicate when to use this tool versus alternatives like ha_get_entity for current state. No exclusions or alternative names are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully cover behavioral traits. It mentions 'resolving device→area inheritance', but does not disclose permissions, side effects, or rate limits. More detail on inheritance resolution behavior is needed for safe usage.
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?
The description is one sentence of 16 words, with no filler. Every word contributes to explaining the tool's purpose and parameter usage.
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?
For a simple tool with one parameter and no output schema, the description covers the core functionality. However, without annotations, additional details about inheritance resolution behavior and expected output format would increase completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'area' has no description in the schema (0% coverage). The description adds that it accepts 'name or area_id', providing essential semantic context beyond the schema's 'string' type, fully compensating for the lack of schema documentation.
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 lists entity_ids for a given area by name or area_id, and mentions resolving device-to-area inheritance. It distinguishes from sibling tools like ha_list_areas (which lists areas) and ha_get_entity (detailed entity data).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to specify the area (by name or area_id) and implicitly when to use the tool (to get entities in a room/area). However, it does not explicitly state when not to use it or mention alternatives like ha_get_states for all entities, which would be clearer guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adequately implies a read operation by stating 'list,' but lacks details on behavior like whether it returns all states without filters, or any limitations.
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?
Single, front-loaded sentence with no unnecessary words; every part earns its place.
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 no output schema and 0% schema coverage, the description omits critical details about return format (structure of each state), which an agent needs to correctly parse results.
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?
Despite 0% schema description coverage, the description adds meaningful context for parameters: domain examples and area clarification (room name or area_id), though could be more precise for domain values.
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?
Description clearly states the tool lists Home Assistant entity states with optional filtering by domain and area, distinguishing it from siblings like ha_get_entity (single) and ha_get_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for listing states with optional filters but no explicit guidance on when to use this tool versus alternatives like ha_get_entities_by_area or ha_get_history, and no when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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. It only states the basic operation without any behavioral details such as authentication requirements, rate limits, or the structure of the returned data. For a read-only list operation, some transparency is implied, but the description does not explicitly confirm safety or format.
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?
The description is a single sentence of 10 words, front-loading the verb 'List'. It is perfectly concise with no wasted words, and every word earns its place.
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?
Given the tool has no parameters and no output schema, the description minimally fulfills completeness by stating the scope. However, it does not describe the return format (e.g., list of names, objects) or any edge cases. For a simple tool, this is adequate but not fully complete.
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?
The tool has zero parameters, and the schema coverage is 100% (no undocumented params). Per baseline rules, this scores a 4. The description adds no parameter information, which is acceptable since there are none.
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?
Description clearly states the tool's purpose: listing all areas/rooms in Home Assistant. It uses a specific verb ('List') and resource ('areas/rooms'), and is distinct from sibling tools that deal with services, config, or entities.
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 does not explicitly state when to use this tool vs alternatives, but the purpose is clear enough that the agent can infer it's for getting a complete list of areas. Sibling tools like ha_get_entities_by_area serve different purposes, so ambiguity is low.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits beyond the fact it retrieves configuration. It lacks details on read-only nature, authentication, or side effects, but the simplicity reduces concern.
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?
The description is a single sentence, front-loads the action, and lists key fields without any unnecessary verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, no-output-schema tool, the description adequately explains what the output contains (version, location, unit system, time zone, loaded components). However, it could mention the response format.
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?
There are no parameters, and schema coverage is 100%, so the baseline is 3. The description adds value by listing what the returned configuration includes, justifying a slightly higher score.
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 gets Home Assistant configuration and lists specific fields (version, location, etc.), distinguishing it from sibling tools that handle individual entities or states.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided, though the description implies it's for global config retrieval, and sibling names hint at alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![ha-mcp MCP server](https://glama.ai/mcp/servers/qubit999/ha-mcp/badges/card.svg)](https://glama.ai/mcp/servers/qubit999/ha-mcp)

Score Badge

Copy to your README.md:

[![ha-mcp MCP server](https://glama.ai/mcp/servers/qubit999/ha-mcp/badges/score.svg)](https://glama.ai/mcp/servers/qubit999/ha-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/qubit999/ha-mcp'

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