Comprehensive Model Context Protocol server for managing Home Assistant through AI assistants.
io.github.homeassistant-ai/ha-mcp — Model Context Protocol Server
The io.github.homeassistant-ai/ha-mcp server is a comprehensive Model Context Protocol (MCP) server for managing Home Assistant through AI assistants. It is described as supporting a large set of tools (indicated as “95+ Tools”), with documented changes including a breaking update related to ha_config_set_yaml.
🛠️ Key Features
Model Context Protocol (MCP) server
Home Assistant management via AI assistants
Broad tool coverage (listed as 95+ Tools)
Breaking change (v7.3.0): ha_config_set_yaml moved to beta
🚀 Use Cases
Managing Home Assistant resources using AI assistants
Using beta documentation for ha_config_set_yaml after v7.3.0
⚡ Developer Benefits
MCP integration for AI-driven Home Assistant workflows
Clear breaking-change note for ha_config_set_yaml relocation to beta
Breaking change (v7.3.0):ha_config_set_yaml has been moved to beta.
The Unofficial and Awesome Home Assistant MCP Server
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with Home Assistant.
Using natural language, control smart home devices, query states, execute services and manage your automations.
Demo with Claude Desktop
🚀 Get Started
The recommended way to run ha-mcp is the HA-MCP Custom Component. It installs into Home Assistant through HACS, runs the full server in-process, and works on every Home Assistant installation type — Home Assistant OS, Supervised, Container, and Core — with full feature parity. It is the easiest setup in every case, with no access token to manage.
Add it to Home Assistant via HACS (the preferred install):
Quick start:
Install the HA-MCP Custom Component from HACS — click the badge above, or in HACS open Integrations → ⋮ → Custom repositories, add https://github.com/homeassistant-ai/ha-mcp-integration (category: Integration), then Download.
Restart Home Assistant.
Go to Settings → Devices & Services → Add Integration, search for HA-MCP Custom Component, choose HA-MCP Server, and click Submit. Creating the entry starts the server.
Copy the connect URL from the entry's Configure screen (Settings → Devices & Services → HA-MCP Custom Component → HA-MCP Server → Configure) — it is also printed in the Home Assistant log. A notification confirms the server started and points you there.
Paste that URL into your AI client — done.
Connect URL. The Configure screen gives you a Home Assistant webhook URL for remote clients — https://<your-ha-domain>/api/webhook/<webhook-id> through Nabu Casa or any reverse proxy already pointed at Home Assistant (locally, http://<ha-host>:8123/api/webhook/<webhook-id>). For clients on the same network, the server is also reachable directly at http://<ha-ip>:9584/private_<random>.
Replaces other install methods: the in-process server is a complete, standalone ha-mcp install — it takes the place of the app (add-on), Docker, and uvx/PyPI (stdio) methods. Run only one; do not run the in-process server alongside another install.
Local only? Turn off Remote access via webhook in the entry options — no webhook is registered at all, while the direct port and sidebar panel keep working.
Settings panel: while the server runs, an admin-only HA-MCP panel appears in the Home Assistant sidebar for managing tools, feature flags, backups, and themes.
Optional authentication: set Webhook authentication to ha_auth to require a Home Assistant account sign-in instead of using the secret URL as the credential.
Manual install (no HACS): copy custom_components/ha_mcp_tools/ from this repository into your Home Assistant config/custom_components/ directory, then restart and add the integration as above.
The component's second entry type, the File & YAML services entry (HA-MCP File & YAML Tools), is only needed if you enable ha-mcp's opt-in file and YAML editing tools (feature flags, off by default) — skip it otherwise; you can add it later at any time. It works with any server type (in-process, app, Docker, or stdio).
Prefer to run ha-mcp as a Home Assistant app (add-on)? On Home Assistant OS and Supervised installs it is a close second — no access token to manage, and it works with Claude Desktop, Claude.ai, ChatGPT, and any other MCP client on your local network or configured for remote access.
Add the repository to your Home Assistant instance:
If that opens the App store without an add-repository dialog (a known Home Assistant issue), add it manually: Settings → Apps → Install app → ⋮ → Repositories, then paste https://github.com/homeassistant-ai/ha-mcp.
Install "Home Assistant MCP Server" from Settings → Apps → Install app and click Start. (Home Assistant 2026.2 renamed "Add-ons" to "Apps"; on older versions this is the Add-on store.)
Open the Logs tab to find your unique MCP URL.
Connect your AI client to that URL — no token or credential setup needed.
⚠️ Configure exactly one install method per client. The custom component, the app, Docker/PyPI, and local stdio are independent ways to run the same server — pick one and point your AI client at that single URL. Keeping two entries for the same server in one client (for example a local uvx ha-mcp@latest entry with HOMEASSISTANT_URL / HOMEASSISTANT_TOKEN alongside an app or component URL) is a known cause of connection hangs.
Other install methods
These run the server outside Home Assistant — useful for Container / Core installs (which can't run apps) or a separate host. The Setup Wizard generates the exact client-specific config for each.
Docker (HTTP server): run ghcr.io/homeassistant-ai/ha-mcp in HTTP mode, pointed at your Home Assistant URL and a long-lived token, and connect your client to its secret URL. See the Setup Wizard for the full command and per-client config.
PyPI / uvx (HTTP server): run the published ha-mcp package with uvx ha-mcp@latest (or pip) as a streamable-HTTP server the same way. Details in the Setup Wizard.
Local stdio (not recommended): runs ha-mcp on your own machine over stdio. The one-command installers in the Demo server section below use this path; the Setup Wizard covers connecting it to your own Home Assistant.
OIDC authentication: gate remote access behind an external identity provider (Authentik, Keycloak, Auth0, etc.) instead of a secret URL — all authenticated users share the server's Home Assistant credentials. See OIDC Mode.
⚠️ stdio has known transport issues. The stdio transport has connection problems that streamable HTTP does not (#1713). It is recommended only for demo/testing tinkering — for a real setup, use the custom component or an HTTP method above.
Using the HA-MCP custom component? You do not need the Webhook Proxy — the component has its own built-in webhook for remote access (see the Get Started quick start at the top). The proxy is for the app (it can also front another external server via its mcp_server_url option). The OpenAI Tunnel below is different: it applies to any install method when Home Assistant isn't publicly reachable at all (no Nabu Casa or reverse proxy).
Already have Nabu Casa or another reverse proxy pointing at your Home Assistant? The Webhook Proxy app routes MCP traffic through your existing setup — no separate tunnel or port forwarding needed.
Install the MCP Server app (see above) and the Webhook Proxy app from the same store
Start the webhook proxy and restart Home Assistant when prompted
Copy the webhook URL from the app logs:
code
MCP Server URL (remote): https://xxxxx.ui.nabu.casa/api/webhook/mcp_xxxxxxxx
Configure your AI client with that URL
For other remote access methods (Cloudflare Tunnel, custom reverse proxy), see the Setup Wizard.
ChatGPT / Codex behind a firewall (OpenAI Tunnel). ChatGPT connectors normally require a publicly reachable URL. If you can't (or don't want to) expose one, the community OpenAI Tunnel for HA-MCP integration by @norpol runs OpenAI's tunnel-client inside Home Assistant and connects your local MCP server URL to an OpenAI-hosted tunnel over an outbound-only connection — no port forwarding, reverse proxy, or public URL. Point it at your ha-mcp URL, then attach the ChatGPT connector to the same tunnel ID. See the FAQ entry and #1811.
Want to try ha-mcp before connecting your own Home Assistant? No paid subscription required. These one-command scripts set up a local stdio connection to a hosted demo environment so you can see it working in a few minutes. Each script's Connect your own Home Assistant link then shows how to point it at your instance.
🍎 macOS
Go to claude.ai and sign in (or create a free account)
Open Terminal and run:
sh
curl -LsSf https://raw.githubusercontent.com/homeassistant-ai/ha-mcp/master/scripts/install-macos.sh | sh
Template helper edit backups capture persisted options through the HA-MCP custom component, using either its Server entry or File & YAML Tools entry. Helper edits, generic integration options edits, and deletion capture the stable config-entry identity and entity ID/name mapping. Capture refuses degraded secret scrubbing. Restoring an existing helper requires a fresh safety backup, removes optional settings absent from the snapshot, and verifies persisted options.
For Template backup listing and bulk deletion, filter by the config-entry ID returned as entity_id by capture. Capture accepts an entity alias; the history filters use the stable config-entry ID. Recreation reports its replacement config-entry ID and saved entity mapping separately.
If the original entry has been deleted, restore recreates the helper and reports its new config-entry ID. The saved entity ID and custom name are restored when available; an occupied entity ID is refused before creation. Older snapshots without entity metadata cannot preserve renamed entity IDs. If a collision or verification failure occurs after creation, the new helper and source backup are retained and the result reports the new entry for inspection. Other entity/device registry settings are not restored. Helper and integration edits through the same server wait until restore finishes; other Home Assistant clients are outside this coordination. Failed or uncertain restores report their outcome and safe refusal reasons; inspect the current helper before retrying.
Home Assistant ships its own MCP Server integration. It is built on the Assist pipeline, so a connected MCP client can read and control the entities you have exposed to Assist and run the intents Assist understands — handy for voice-style control of already-exposed devices.
ha-mcp is a standalone server built for configuring, building, and debugging your smart home, not just controlling it. On top of device control, it adds capabilities the built-in integration does not have:
Capability
Built-in MCP Server
ha-mcp
Control exposed devices, query states
Yes
Yes
Entity scope
Only entities exposed to Assist
Everything in Home Assistant
Create / edit automations, scripts, scenes
No
Yes
Build & edit dashboards
No
Yes
Debug automations from traces, read history & logs
No
Yes
Manage helpers, areas, zones, labels, groups
No
Yes
Backups, apps, HACS, device & entity registry
No
Yes
Rule of thumb: Use the built-in integration for voice-style control of devices you have already exposed; use ha-mcp when you want an AI assistant that can also build and maintain your Home Assistant setup.
The HA-MCP Custom Component also powers a set of privileged tools that standard Home Assistant APIs can't provide: file system access and YAML config editing. (The same component runs the full server in-process — that's the recommended install in the Get Started section at the top.) Its File & YAML services entry (HA-MCP File & YAML Tools) enables the tools below.
Tools that require the component:
Tool
Description
ha_config_set_yaml(beta)
Safely add, replace, or remove top-level YAML keys in configuration.yaml and package files (automatic backup, validation, and config check)
ha_list_files(beta)
List files in allowed directories
ha_read_file(beta)
Read files from allowed paths (config YAML, logs, and allowed directories)
ha_write_file(beta)
Write files to allowed directories
ha_delete_file(beta)
Delete files from allowed directories
Template helper edit backups and restores also require the component, using either its Server entry or File & YAML Tools entry. These five tools return an error with installation instructions if the component is missing.
These tools also require beta feature flags. See Beta Features for how to enable them — including the ENABLE_BETA_FEATURES master flag, which must be on before the filesystem/YAML sub-flags take effect.
Install
Install the HA-MCP File & YAML Tools entry from the same HA-MCP Custom Component:
To add manually: open HACS > Integrations > three-dot menu > Custom repositories > add https://github.com/homeassistant-ai/ha-mcp-integration (category: Integration) > Download. Or copy custom_components/ha_mcp_tools/ from this repository into your HA config/custom_components/ directory.
After installing, restart Home Assistant, then open Settings > Devices & Services > Add Integration, search for HA-MCP Custom Component, and add the HA-MCP File & YAML Tools entry.
To run the full ha-mcp server in-process through this same component, see the Get Started section at the top and the full in-process server documentation →.
🧠 Better Results with Agent Skills
This server gives your AI agent tools to control Home Assistant. For better configurations, pair it with Home Assistant Agent Skills — domain knowledge that teaches the agent Home Assistant best practices.
An MCP server can create automations, helpers, and dashboards, but it has no opinion on how to structure them. Without domain knowledge, agents tend to over-rely on templates, pick the wrong helper type, or produce automations that are hard to maintain. The skills fill that gap: native constructs over Jinja2 workarounds, correct helper selection, safe refactoring workflows, and proper use of automation modes.
Bundled Skills (built-in)
Skills from homeassistant-ai/skills are bundled and served as MCP resources via skill:// URIs. Any MCP client that supports resources can discover them automatically — no manual installation needed. For tool-only clients (claude.ai, etc.), the same skills are reachable through the polymorphic ha_get_skill_guide tool — call it with no args to list bundled skills, with a skill arg to list its files, or with skill + file to read content. Resources are not auto-injected into context — clients must explicitly request them, so idle context cost is just the metadata listing.
ha_get_skill_guide is a mandatory tool: the catalog always exposes it (it can't be disabled) so tool-only clients never see a silently missing skill surface.
Skills can still be installed manually for clients that prefer local skill files — see the skills repo for instructions.
🔍 Tool Discovery for AI Agents
By default, the full tool catalog (~87 tools) is listed to the client through the standard MCP tools/list response. Clients with deferred / on-demand tool loading (claude.ai, Claude Desktop, Claude Code) handle that fine — tools are pulled into context only when needed, so idle context cost is near-zero.
For setups without deferred tool support — models like Claude Haiku, Gemini, OpenAI-compatible local models and smaller open-weights models, or clients that inline all tool schemas regardless of model (e.g. GitHub Copilot CLI) — listing the full tool catalog up front adds a lot of idle context and can overwhelm smaller models. To address that, the server ships with a search-based discovery mode built on top of FastMCP's BM25 search transform.
Smaller or local LLMs (Ollama, etc.)
If your model can't see the tools or your Home Assistant, it may be getting handed the whole tool catalog at once and struggling with it. It's recommended to try the following to see if it helps:
Enable tool search (ENABLE_TOOL_SEARCH=true, or the app option below). Instead of listing every tool up front, the server defers the catalog behind a search interface so the model pulls in only the tools it needs, when it needs them.
Raise the model's context window above the default. Local runtimes ship with small defaults (Ollama's num_ctx is one example) that can't hold a large tool set plus the conversation — increase it well beyond the default.
Enable search-based discovery
Set ENABLE_TOOL_SEARCH=true (or toggle the option in the HA app). The full catalog is replaced in the tool list with four entry points plus a small set of always-visible "pinned" tools (ha_search, ha_get_overview, ha_report_issue, etc.). All tools remain callable directly by name once discovered:
Tool
Purpose
ha_search_tools
BM25 keyword search across all tools. Returns name, description, parameters, and annotations (readOnlyHint / destructiveHint) so the agent can pick the right one.
ha_call_read_tool
Execute a readOnlyHint tool by name. Safe — clients can auto-approve.
ha_call_write_tool
Execute a write tool that creates or updates data.
ha_call_delete_tool
Execute a tool that removes / deletes data.
The proxy split lets MCP clients apply different permission policies per category (e.g. auto-approve reads, prompt for writes, confirm deletes) without parsing tool docstrings.
A ha_manage_* tool combines several operations, so it is reachable from more than one proxy: ha_call_write_tool and ha_call_delete_tool run the whole tool, while ha_call_read_tool runs only the read actions Read Only Mode approves (the same per-call verdict), so a manage tool with no approved read actions is not reachable there. Search results list each proxy the tool can be reached through. In Read Only Mode only ha_call_read_tool is listed; the other two still answer a client that holds them in a cached tool list, and any write they carry gets the Read Only Mode error rather than Unknown tool.
Setting
Default
Description
ENABLE_TOOL_SEARCH
false
Replace full tool catalog with search-based discovery (tools deferred behind on-demand search).
TOOL_SEARCH_MAX_RESULTS
5
Max results returned by ha_search_tools (range 2–10).
PINNED_TOOLS
empty
Comma-separated tool names to keep always visible. The web settings UI is the primary way to manage this.
When to enable
Claude Haiku, OpenAI-compatible local models, Gemini, or any model without native deferred tool support — large idle-context savings. The same applies to clients that inline all tool schemas regardless of model (e.g. GitHub Copilot CLI, even when running Claude Sonnet/Opus).
MCP clients that cap total tool count (some cap at 100) — surfaces a minimal set (~10 tools) instead of 87.
Cost-sensitive deployments — fewer idle tokens per turn.
Leave it off in clients with deferred tool loading (claude.ai, Claude Desktop, Claude Code); the full catalog has no idle cost there, direct calls skip the search step, and the client's built-in tool search is the better choice — there is no benefit to running ha-mcp's on top of it. Whether tools are deferred depends on the client and model combination: the same model can behave differently per client — GitHub Copilot CLI running Claude Sonnet/Opus inlines the full catalog and still benefits from tool search here. Some Codex models and ChatGPT include deferred tools too — check your client/model directly to confirm its features so you don't leave this enabled unnecessarily.
🔄 Refresh your client's tool list after changing this (or any) setting. Toggling ENABLE_TOOL_SEARCH (or changing pinned/disabled tools, Read Only Mode, etc.) changes the tools the server exposes, but your AI client keeps serving its cached tool list until it re-fetches. Restarting the app or Home Assistant does not refresh the client — reconnect or refresh the MCP server in your client (e.g. re-add/refresh the connector in ChatGPT, or close and reopen Claude Desktop). If you skip this, newly enabled tools won't appear in the client at all, and tools the server no longer exposes still show as available but fail when called (Unknown tool, or the Read Only Mode error for a write tool that mode hides). ChatGPT sometimes keeps serving the stale list even after the connector is removed and re-added under the same name — if tools are still missing after re-adding, delete the connector and create a new one with a different name.
For the HA app, the same option is documented in homeassistant-addon/DOCS.md along with the in-app settings UI for fine-grained tool enable/disable/pin.
Read-only HTTP connections
Append /readonly to the server's HTTP MCP endpoint to restrict that connection
to the existing Read Only Mode while other clients keep normal access:
OAuth and OIDC connections use the same login/provider: for example,
https://example.com/mcp/readonly. No additional secret or server is required.
Read-only connections hide write tools and block write calls, including calls
through cached tools or search proxies. The global Read Only Mode setting still
restricts both endpoints when enabled. Reconnect the client after changing its URL
so it refreshes its tool list.
This is a connection mode for automated agents, not a separate permission on the
credential: the same credentials still work at the normal endpoint. Home Assistant
webhook URLs also accept the suffix:
https://your-ha.example/api/webhook/<webhook-id>/readonly. This requires the
updated embedded integration or Webhook Proxy dev app (add-on), together with
the updated MCP server.
🧪 Dev Channel
Want early access to new features and fixes? Dev releases (.devN) are published on every push to master.
For development setup, testing instructions, and contribution guidelines, see CONTRIBUTING.md.
For comprehensive testing documentation, see tests/README.md.
🔒 Privacy
Ha-mcp runs locally on your machine. Your smart home data stays on your network.
No telemetry today — anonymous usage stats are a planned future feature (as of June 2026); when it lands it will follow your Home Assistant analytics/telemetry setting (which you can override), announced prominently in the release notes and the web Settings UI at least one month beforehand
No personal data collection — we never collect entity names, configs, or device data
User-controlled bug reports — only sent with your explicit approval
@knowald — Area resolution via device registry in ha_get_system_overview for entities assigned through their parent device. Financial support via GitHub Sponsors. Thank you! ☕
@TomasDJo — Category support for automations, scripts, and scenes.
@bzelch — python_transform support for automations and scripts.
@gcormier — Windows installer improvements: removed unused variable and fixed terminal closing after install.
@ekobres — Feature flags for HAMCP_ENABLE_FILESYSTEM_TOOLS and the (since removed) HAMCP_ENABLE_CUSTOM_COMPONENT_INTEGRATION in the app config, with beta tagging in source and docs.
@griffinmartin — Added OpenCode (by Anomaly) as a selectable AI client in the setup wizard, with both stdio and streamable HTTP support.
@hhopke — Fixed app (add-on) API calls to route through HA Core ingress proxy instead of direct container connections, fixing ha_manage_addon (now ha_manage_app) proxy mode on app installs.
@tomwilkie — JMESPath middleware exploration (#1147) whose review-time token-measurement data informed the design of #1199 and #1225.
@SealKan — fields=/attribute_keys= projection on six read-heavy tools (#1225), ha_call_event tool (#1239), dashboards-list helper refactor (#1207), for:-field duration-math detector in the best-practice checker (#1264), persistent DCR OAuth client registrations across restarts (#1265), and issue-triage prompt token-budgeting (#1522).
@KarelTestSpecial — Cached YAML instance to prevent CPU spikes during bulk edits (#1371).
@corgan2222 — HA brand assets for custom integration (#1317).
@drseanwing — Progress emission via FastMCP Context in long-running tools (#1124); tool-discovery / categorized-search docs (#1123).
@fnordpig — Config subentry support (#1393) and Assist pipeline management tool (#1392).
@paul43210 — array_patch mode in ha_manage_app for atomic GET-modify-POST (#1063).
@L1AD — Filed #966 proposing tool security policies; pointed to PolicyLayer's MCP-security work as prior art that inspired the predicate DSL shape.
@nightcityblade — Updated stale Home Assistant Advanced Mode references after HA 2026.6 made formerly advanced options available by default (#1533).