Telldone

TellDone MCP Server

Connect your TellDone voice notes, tasks, events, and reports to Claude (Desktop, claude.ai, and Code), Cursor, Windsurf, Codex, and any MCP-compatible client — with one-click OAuth (browser sign-in, no token to copy) or a bearer token.

TellDone is a voice-first planning app. Dictate your thoughts, and AI automatically creates structured notes, tasks, events, and daily productivity reports.

Voice recording is available on iOS and Apple Watch. Android coming soon. You can also send text through MCP using process_note for the same AI analysis pipeline.

Use promo code `MCPBETA26` after signup to get free MCP access (read & write for 30 days, then read-only for a year).

Quick Start

Connect in one of two ways: one-click OAuth (recommended — browser sign-in, nothing to copy) or a bearer token (works with every MCP client).

Option A — One-click OAuth · Claude Desktop, claude.ai, Claude Code

Add TellDone as a connector, sign in to your account in the browser, and approve. Access tokens are short-lived, scope-limited, and revocable any time in Settings — there's nothing to copy or store.

Claude Desktop & claude.ai — in Settings, open Connectors, choose Add custom connector, and paste:

https://api.telldone.app/mcp/user

Click Connect, sign in to TellDone, and approve the access. No manual app registration — TellDone supports Client ID Metadata Documents, so Claude registers itself automatically.

Claude Code

claude mcp add --transport http telldone https://api.telldone.app/mcp/user

Then run /mcp and choose telldone → Authenticate to open the TellDone consent page in your browser — sign in and approve once. (CLI v2.1.186+: claude mcp login telldone does the same from the shell.)

Any MCP client that supports OAuth 2.1 discovery (RFC 9728 + RFC 8414) connects the same way.

Option B — Bearer token · Cursor, Windsurf, Codex, or any client

First get a token: sign up at app.telldone.app, open Settings → AI Agents (MCP), and click Enable. Then add the server with your token:

Claude Code

claude mcp add telldone --transport http \

https://api.telldone.app/mcp/user/mcp \ --header "Authorization: Bearer YOUR_TOKEN"

Cursor .cursor/mcp.json

{

"mcpServers": { "telldone": { "url": "https://api.telldone.app/mcp/user/mcp", "headers": { "Authorization": "Bearer YOUR_TOKEN" } } } }

Windsurf .codeium/windsurf/mcp_config.json

{

"mcpServers": { "telldone": { "serverUrl": "https://api.telldone.app/mcp/user/mcp", "headers": { "Authorization": "Bearer YOUR_TOKEN" } } } }

Codex codex.json

{

"mcpServers": { "telldone": { "type": "http", "url": "https://api.telldone.app/mcp/user/mcp", "headers": { "Authorization": "Bearer YOUR_TOKEN" } } } }

OpenClaw Settings > MCP Servers > Add > Name: TellDone, URL: https://api.telldone.app/mcp/user/mcp, Auth: Bearer YOUR_TOKEN

Start Using

Ask your AI tool things like:

• *"What did I work on today?"*
• *"Create a task: review quarterly report, high priority, deadline Friday"*
• *"Find all notes about the marketing strategy"*
• *"Mark the Figma task as done"*
• *"Create an event: team standup tomorrow at 10am, remind me 15 min before"*
• *"Process this meeting summary and extract tasks"*
• *"What events do I have next week?"*
• *"Show me my daily report from yesterday"*

Data Formats — Read This Before Parsing Output

Every tool returns JSON. The MCP wire response wraps payloads in result.content[0].text as a JSON-encoded string — parse it with json.loads() (or equivalent) to get the actual data.

All datetimes, dates, and UUIDs in the decoded JSON are STRINGS, not native language types. Do not call .toordinal(), .weekday(), or any datetime method directly on them — you will get TypeError: 'str' has no attribute 'toordinal'. Parse them first.

Scalar output types

Array / object output types

Enum values

• priority — "low", "medium", "high", or null
• note.type — "task", "idea", "info", "status", "meeting", "event", "reflection"
• note.status — "active", "archived" (deleted records are excluded from every read tool)
• task.status — "todo", "done" (query param status="all" means "all not-deleted")
• event.status — "confirmed", "tentative", "cancelled"
• report.type — "daily", "weekly", "monthly", "yearly"
• source (tasks), completed_by (tasks) — free-form strings: "mcp", "app", "sync", "audio", "todoist", "notion", etc.

Per-tool output fields

Input parameter formats

• note_id, task_id, event_id, parent_*_id — UUID strings
• date_from, date_to, deadline — YYYY-MM-DD strings (empty string means "no filter")
• start_at, end_at, reminder_at — ISO 8601 datetime strings, e.g. "2026-04-15T09:00:00Z" or "2026-04-15T09:00:00+00:00"
• tags — comma-separated string on input (e.g. "work,urgent"); stored/returned as string[]
• reminder_minutes, attendees — comma-separated strings on input; stored/returned as arrays
• is_all_day — boolean on create_event; string "true"/"false" on update_event
• recurrence_rule — RRULE string, e.g. "FREQ=WEEKLY;BYDAY=MO,WE,FR"

Parsing example (Python)

import json

from datetime import datetime, date

tools/call response → text → decode

payload = json.loads(response"result"0)

Check for error first

if "error" in payload: raise RuntimeError(payload["error"])

Events: start_at is a STRING like "2026-04-18T11:30:00+00:00"

for e in payload: # payload is list from get_events start = datetime.fromisoformat(e["start_at"]) # -> tz-aware datetime if e["end_at"]: end = datetime.fromisoformat(e["end_at"])

Tasks: deadline is a STRING like "2026-04-18" (date only)

for t in tasks_payload: if t["deadline"]: d = date.fromisoformat(t["deadline"]) days_left = (d - date.today()).days

Note Fields: title, summary, transcript

Every note has three text fields with different roles and different limits. Choosing the right field matters — LLM clients (Claude Desktop, Cursor, etc.) should split content appropriately when using create_note or update_note.

Plan-based transcript limits (subscription_plans.max_text_length):

Rule of thumb for LLM clients:

• Short output (notes, reminders, todos): just title + summary. Leave transcript empty.
• Long output (meeting notes, drafts, brainstorms, research dumps): put a 1–3 sentence summary and the full body in `transcript`. Do not pack everything into summary — you'll hit the 1000-char error.

Overflow error messages:

• summary too long (max 1000 chars, got N). For long-form content use the 'transcript' parameter (plan-based limit).
• transcript too long (max 20000 chars for pro plan, got N)

Correct usage example (Claude Desktop captures a meeting):

create_note({

title: "Weekly engineering sync — API versioning", summary: "Team agreed on semver deprecation policy with 6-month sunset window. Owner: Alex. Next sync: Thu.", transcript: "Full meeting transcript: Alice raised the question of how to deprecate v1...\n\n[... 5 KB of detail ...]", tags: "engineering,versioning,meeting" })

Why two different caps?

• summary is included verbatim in daily/weekl