Integration

Habitify integration

Habitify is a habit tracker. Through its v2 API an agent can list, create, update, archive and delete habits, read the daily habit journal and per-habit statistics, record progress (log a value, mark a habit completed, failed or skipped for a date, or undo a day), manage notes attached to a habit, and organise habits into areas. API access requires a paid Habitify subscription. Authentication is an API key generated in the Habitify app (Settings > API) and sent in the X-API-Key header; only one key is active at a time.

Connect Habitify How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Habitify.Built from the 24 Habitify tools below, on the connection you add once.

What you can do with Habitify

Each of these is one operation on one endpoint, available both as a workflow step and as a tool an AI agent can call on its own. Nothing bundles several operations into one action, so what a run did stays readable afterwards.

Most endpoints run on the free plan. A few, mainly the ones that publish on your behalf, need a paid plan.

Habit, 10 operations

archive_habitArchive habitPOSTArchives a habit: it is hidden from the active habits list and keeps all its data. Archived habits stay readable through list_habits with archived=true.
complete_habitComplete habitPOSTMark a habit as completed for a specific date. The system automatically computes the appropriate log value based on the habit's goal or target.
create_habitCreate habitPOSTCreates a habit. name and type (good or bad) are required; occurrence, goal, reminders, endCondition, areaIds and timeOfDayIds are optional. Returns the created habit with its id.
delete_habitDelete habitDELETEPermanently deletes a habit with all its logs, notes, goals and reminders; this cannot be undone. To hide a habit and keep its data, use archive_habit instead.
fail_habitFail habitPOSTMark a habit as failed for a specific date. The system automatically records a failure log value.
get_habitGet habitGETRetrieve the full details of a specific habit by its ID, including goals, reminders, areas, and configuration.
list_habitsList habitsGETReturns a paginated list of your habits (limit 1-100, default 50, with offset). Filter by archived status, area (areaId), type (good or bad) or time-of-day period id.
skip_habitSkip habitPOSTMark a habit as skipped for a specific date. Use this when you intentionally decide not to perform the habit for the day.
undo_habit_logsUndo habit logsPOSTRemove all log entries for a habit on a specific date, effectively resetting the habit's status to in-progress for that day.
update_habitUpdate habitPUTUpdate the properties of an existing habit. Only the fields provided in the request body are updated; omitted fields remain unchanged.

Area, 5 operations

create_areaCreate areaPOSTCreate a new area for organizing and categorizing habits.
delete_areaDelete areaDELETEPermanently delete an area. Habits assigned to this area will be unassigned but not deleted.
get_areaGet areaGETRetrieve the details of a specific area by its ID.
list_areasList areasGETReturns all your areas (the groups that organise habits) with id, name, color and icon. Pass an area id as areaId to list_habits, or in areaIds when creating or updating a habit.
update_areaUpdate areaPUTUpdate the properties of an existing area. Only the fields provided in the request body are updated.

Habit note, 4 operations

create_habit_noteCreate habit notePOSTAdds a note to a habit. Give at least one of content, moodLevel or photos (a list of photo URLs).
delete_habit_noteDelete habit noteDELETEPermanently delete a note from a habit. This action cannot be undone.
list_habit_notesList habit notesGETReturns the notes attached to a habit (text content, mood level, photo URLs), ordered by creation date.
update_habit_noteUpdate habit notePUTUpdate an existing note for a habit. At least one field must be provided. Only the fields included in the request body are updated.

Habit log, 3 operations

create_habit_logCreate habit logPOSTRecords a measured value for a habit (for example 5 kM or 30 min) on a date, default today. Use complete_habit instead to simply mark it done.
delete_habit_logDelete habit logDELETEPermanently delete a specific log entry by its ID. This removes the recorded value from the habit's tracking history.
list_habit_logsList habit logsGETRetrieve a paginated list of log entries for a specific habit, optionally filtered by an inclusive date range. Logs are ordered from newest to oldest.

Habit journal, 1 operation

get_habit_journalGet habit journalGETRetrieve all your habits with their completion status and progress for a specific date.

Habit statistics, 1 operation

get_habit_statisticsGet habit statisticsGETReturns aggregated statistics for one habit over an optional date range (default: the habit's start date to today): completions, skips, fails, total logged value, average per day and a day-by-day breakdown.

Use Habitify from Claude Code, Cursor or Codex

Connect Habitify in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Habitify operations become tools the client can call, next to every other integration you connected.

Claude Code

claude mcp add --transport http livecontext https://livecontext.ai/mcp --header "X-API-Key: YOUR_API_KEY"

Codex (~/.codex/config.toml)

[mcp_servers.livecontext]
url = "https://livecontext.ai/mcp"

[mcp_servers.livecontext.http_headers]
"X-API-Key" = "YOUR_API_KEY"

Cursor, Claude Desktop and other JSON configs

{
  "mcpServers": {
    "livecontext": {
      "type": "http",
      "url": "https://livecontext.ai/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Set up the MCP server step by step

How to connect Habitify

Create your workspace
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Connect Habitify once
Add your Habitify connection in Settings. Every tool from this integration reuses it, and secrets are encrypted at rest and visible only to you.
Describe the job in chat
The workflow builds itself in front of you and picks the endpoints it needs. Drag the steps yourself on the canvas whenever you would rather be explicit.