TellDone
Voice-first planning app. Dictate voice notes on iOS/Apple Watch, AI creates structured tasks and events. 21 MCP tools (read + write). Connect from Claude Code, Cursor, Windsurf. Free trial with promo code MCPBETA26.
TellDone MCP Server
Connect your TellDone voice notes, tasks, events, and reports to AI tools like Claude Code, Cursor, Windsurf, Codex, and any MCP-compatible client.
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
MCPBETA26after signup to get free MCP access (read & write for 30 days, then read-only for a year).
Quick Start
1. Get Your Token
Sign up at app.telldone.app, then go to Settings > AI Agents (MCP) and click Enable.
2. Connect
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
3. 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
| Field shape | Wire format | Example | Parse with |
|---|---|---|---|
| UUID | string (lowercase hex with dashes) | "b3f3c8a0-9a4d-4e12-9f4a-1a1b2c3d4e5f" | use as-is |
| Datetime (timestamp) | ISO 8601 string with timezone offset | "2026-04-18T11:30:00+00:00" | datetime.fromisoformat(s) in Python; new Date(s) in JS |
| Date (calendar day, no time) | YYYY-MM-DD string | "2026-04-18" | date.fromisoformat(s) in Python |
| Boolean | true / false | true | native |
| Integer | JSON number | 42 | native |
| Nullable field | JSON null | null | None / null |
Array / object output types
| Field | Wire format |
|---|---|
tags (on notes/tasks/events) | array of strings, OR null if never set, OR [] if cleared |
reminder_minutes (events, writable field) | array of ints on input/output |
attendees (events, writable field) | array of strings (names/emails) |
metadata (notes) | JSON object or null |
tasks / events arrays inside get_note / get_notes_full | always present, possibly empty [] |
Enum values
priority—"low","medium","high", ornullnote.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 paramstatus="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
| Tool | Returned fields (all at top level of each array item unless noted) |
|---|---|
get_profile | id UUID, email str, display_name str|null, locale str, transcription_locale str|null, timezone str (IANA), subscription str, mcp_mode str, created_at ISO 8601 datetime str, stats {notes:int, tasks:int, events:int} |
get_notes | id UUID, title str, summary str|null, type enum, tags str[]|null, priority enum|null, status enum, recorded_at ISO 8601 datetime str|null, created_at ISO 8601 datetime str |
get_note | note fields (id, title, summary, transcript str|null, type, tags, priority, status, metadata obj|null, created_at) + tasks[] + events[] arrays with subset fields |
get_notes_full | array of notes with tasks[] and events[] embedded (same subset as get_note, minus metadata) |
get_tasks | id UUID, title str, description str|null, status enum, priority enum|null, tags str[]|null, deadline YYYY-MM-DD str|null, reminder_at ISO 8601 datetime str|null, completed_at ISO 8601 datetime str|null, completed_by str|null, source str|null, created_at ISO 8601 datetime str |
get_events | id UUID, title str, description str|null, status enum, start_at ISO 8601 datetime str (non-null), end_at ISO 8601 datetime str (non-null), location str|null, is_all_day bool|null, tags str[]|null, created_at ISO 8601 datetime str. Note: attendees, reminder_minutes, recurrence_rule are writable via create_event/update_event but are NOT returned by get_events. |
get_reports | id UUID, type enum, period_start YYYY-MM-DD str, period_end YYYY-MM-DD str, content_md str|null, created_at ISO 8601 datetime str |
get_tags | tag str, usage_count int, is_pinned bool, is_manual bool |
search | {notes: [...], tasks: [...], events: [...]} — each item is {id UUID, type "note"/"task"/"event", title str, detail str|null, created_at ISO 8601 datetime str}. All three arrays always present, possibly empty. |
| Write tools | minimal: {id UUID, title str, status enum} (plus type on notes). Do not expect full records — call the matching get_* tool if you need more fields. |
| Delete tools | {id UUID, deleted: true} |
process_note | {audio_id UUID, status "processing", mode "audio+stt"/"text-only", message str} — async; final result arrives via WebSocket note_ready or a later get_notes call. |
| Any tool on error | {error: "message"} — always null-check for the error key before treating the response as a record. |
Input parameter formats
note_id,task_id,event_id,parent_*_id— UUID stringsdate_from,date_to,deadline—YYYY-MM-DDstrings (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 asstring[]reminder_minutes,attendees— comma-separated strings on input; stored/returned as arraysis_all_day— boolean oncreate_event; string"true"/"false"onupdate_eventrecurrence_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"]["content"][0]["text"])
# 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.
| Field | Role | Limit | Included in report LLM prompts? |
|---|---|---|---|
title | One-line subject shown in lists, previews, push, email subjects. | 200 chars | ✅ (as list header) |
summary | 1–3 sentence teaser. | Hard cap 1000 chars — product decision. | ✅ Verbatim. Keep it concise. |
transcript | Full note body. Shown in detail view. | Plan-based (see below) | ❌ Never. Safe to be long. |
Plan-based transcript limits (subscription_plans.max_text_length):
| Plan | Max transcript chars |
|---|---|
| Free | 2 000 |
| Basic | 8 000 |
| Pro | 20 000 |
| Ultra | 50 000 |
| Custom | 100 000 |
Rule of thumb for LLM clients:
- Short output (notes, reminders, todos): just
title+summary. Leavetranscriptempty. - Long output (meeting notes, drafts, brainstorms, research dumps): put a 1–3 sentence
summaryand the full body intranscript. 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?
summaryis included verbatim in daily/weekly/monthly report LLM prompts. If every summary could be 20 KB, report prompts would blow up in cost and latency (and risk context-window overflow for heavy users). 1000 chars was set in April 2026 after measuring prod data (median 247, max 554).transcriptis never in report prompts — it only shows up in the UI detail view. Large transcripts cost only storage, not LLM tokens. Capping by plan prevents abuse but otherwise lets you be generous.
Backward compatibility: transcript is an optional parameter (default ""). Old clients calling create_note(title, summary, tags, type) continue to work unchanged — the database stores transcript = NULL. No migration needed.
Tools (20)
All tools include MCP annotations — title, readOnlyHint, destructiveHint, idempotentHint, openWorldHint — so MCP clients can surface the right confirmation UI. Every tool runs against the Telldone database only (openWorldHint: false) — the server never reaches out to external APIs.
Read Tools (9)
| Tool | Description |
|---|---|
get_profile | Returns the authenticated user's profile including display name, email, locale, timezone, subscription plan, and usage statistics (total notes, tasks, events). Use this to check account status or quota. |
get_notes | Lists voice notes with optional filters: date_from/date_to (ISO 8601), tag (string), type (task/idea/info/status/meeting/event/reflection), search (text query), limit (default 20, max 100), offset. Returns note metadata without full body — use get_note for details. |
get_note | Returns a single note by UUID note_id, including full transcription, AI summary, and all linked child tasks and events. Use when you need complete note content after finding it via get_notes or search. |
get_notes_full | Bulk retrieval of notes with embedded children (tasks + events). Same filters as get_notes. Use instead of calling get_note in a loop. Returns larger payloads — set limit appropriately. |
get_tasks | Lists tasks with filters: status (todo/done/all, default: todo), tag, priority (low/medium/high), date_from/date_to for deadline range, limit, offset. Returns title, priority, deadline, reminder_at, tags, completion status. |
get_events | Lists calendar events with date_from/date_to range filters, status (confirmed/tentative/cancelled), limit, offset. Returns event title, start/end times, location, attendees, and reminders. |
get_reports | Returns AI-generated productivity reports. Filter by period (daily/weekly/monthly/yearly) and date_from/date_to. Reports summarize completed tasks, patterns, and productivity insights. |
get_tags | Returns all user-defined tags sorted by usage frequency (most used first). No parameters. Use to discover available tags before filtering notes or tasks. |
search | Hybrid text + semantic search across notes, tasks, and events. Parameter: query (string). Combines keyword matching with vector similarity for relevant results even with different wording. Returns mixed result types with relevance scores. |
Write Tools (11)
| Tool | Description |
|---|---|
process_note | Runs the full AI analysis pipeline on text or audio input — identical to recording a voice note in the mobile app. Accepts text (string) or audio_base64 + audio_format (m4a/wav/mp3). AI extracts structured note + tasks + events + tags. Returns immediately with audio_id; results arrive asynchronously. Poll with get_notes() to retrieve processed output. |
create_note | Creates a plain text note without AI analysis. Parameters: title (required, max 200), summary (max 1000 chars, concise teaser — included in report LLM prompts), transcript (plan-based limit, long-form body — NOT in report prompts), type (task/idea/info/status/meeting/event/reflection), tags (comma-separated, max 20). See Note Fields section for where to put long text. |
create_task | Creates a task with title (required), description, priority (low/medium/high, default: medium), deadline (ISO 8601 date), reminder_at (ISO 8601 datetime), tags (comma-separated). Task is created with status "todo". Syncs to mobile app in real-time. |
create_event | Creates a calendar event with title (required), start_at/end_at (ISO 8601 datetime), location, attendees (comma-separated), reminder_minutes (integer), recurrence (rrule string), status (confirmed/tentative). |
update_note | Updates note fields by note_id (UUID, required). Optional: title, summary (max 1000), transcript (plan-based limit, long-form body), type, tags, priority, status. Only provided fields are changed; omitted fields remain unchanged. Pass " " (single space) for summary or transcript to clear the field. |
update_task | Updates task fields by task_id (UUID, required). Optional: title, description, priority, deadline, reminder_at, tags, status (todo/done). Use complete_task as a shortcut for marking done. |
update_event | Updates event fields by event_id (UUID, required). Optional: title, start_at, end_at, location, attendees, status (confirmed/tentative/cancelled), reminder_minutes. |
complete_task | Marks a task as done by task_id (UUID). Shortcut for update_task with status: "done". Records completion timestamp and source ("mcp"). |
delete_note | Soft-deletes a note by note_id (UUID). Cascades to all linked child tasks and events — they are also soft-deleted. Reversible from the web app. |
delete_task | Soft-deletes a task by task_id (UUID). Does not affect the parent note. Reversible from the web app. |
delete_event | Soft-deletes an event by event_id (UUID). Does not affect the parent note. Reversible from the web app. |
All write tools sync in real-time to connected mobile and web clients via WebSocket.
Full Pipeline: process_note
The process_note tool runs the same pipeline as recording in the mobile app:
Text or Audio --> STT (if audio) --> LLM Analysis --> Note + Tasks + Events + Tags
Text mode (skip STT):
{"name": "process_note", "arguments": {"text": "Need to buy groceries. Meeting with Katie at 3pm."}}
Audio mode (base64-encoded):
{"name": "process_note", "arguments": {"audio_base64": "...", "audio_format": "m4a"}}
Returns immediately with audio_id. Results arrive via WebSocket or poll with get_notes().
Examples
examples/test-connection.sh
#!/bin/bash
# Test your TellDone MCP connection
TOKEN="${1:?Usage: ./test-connection.sh YOUR_TOKEN}"
URL="https://api.telldone.app/mcp/user/mcp"
echo "=== Testing connection ==="
curl -s -X POST "$URL" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_profile"}}' \
| python3 -m json.tool
echo ""
echo "=== Listing tools ==="
curl -s -X POST "$URL" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"jsonrpc":"2.0","id":2,"method":"tools/list"}' \
| python3 -c "import sys,json; tools=json.load(sys.stdin).get('result',{}).get('tools',[]); print(f'{len(tools)} tools available'); [print(f' {t[\"name\"]}') for t in tools]"
examples/daily-summary.sh
#!/bin/bash
# Get today's tasks and notes summary
TOKEN="${1:?Usage: ./daily-summary.sh YOUR_TOKEN}"
URL="https://api.telldone.app/mcp/user/mcp"
TODAY=$(date +%Y-%m-%d)
call() {
curl -s -X POST "$URL" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d "$1"
}
echo "=== Today's Notes ($TODAY) ==="
call "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"get_notes\",\"arguments\":{\"date_from\":\"$TODAY\",\"limit\":20}}}" \
| python3 -c "
import sys, json
r = json.loads(json.load(sys.stdin)['result']['content'][0]['text'])
for n in r: print(f' [{n[\"type\"]}] {n[\"title\"]}')" 2>/dev/null
echo ""
echo "=== Active Tasks ==="
call '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_tasks","arguments":{"status":"todo","limit":10}}}' \
| python3 -c "
import sys, json
r = json.loads(json.load(sys.stdin)['result']['content'][0]['text'])
for t in r: print(f' [{t[\"priority\"]}] {t[\"title\"]}')" 2>/dev/null
echo ""
echo "=== Upcoming Events ==="
call "{\"jsonrpc\":\"2.0\",\"id\":3,\"method\":\"tools/call\",\"params\":{\"name\":\"get_events\",\"arguments\":{\"date_from\":\"$TODAY\",\"limit\":5}}}" \
| python3 -c "
import sys, json
r = json.loads(json.load(sys.stdin)['result']['content'][0]['text'])
# NOTE: start_at is a STRING like '2026-04-18T11:30:00+00:00' — parse before date math
for e in r: print(f' {e[\"start_at\"][:16]} {e[\"title\"]}')" 2>/dev/null
examples/create-task.sh
#!/bin/bash
# Create a task via MCP
TOKEN="${1:?Usage: ./create-task.sh YOUR_TOKEN 'Task title'}"
TITLE="${2:?Usage: ./create-task.sh YOUR_TOKEN 'Task title'}"
PRIORITY="${3:-medium}"
curl -s -X POST "https://api.telldone.app/mcp/user/mcp" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"create_task\",\"arguments\":{\"title\":\"$TITLE\",\"priority\":\"$PRIORITY\"}}}" \
| python3 -m json.tool
Plans and Access
| Plan | MCP Access | Read | Write | Price |
|---|---|---|---|---|
| Free | -- | -- | -- | $0 |
| Basic | -- | -- | -- | $4.99/mo |
| Pro | Read & Write | 9 tools | 11 tools | $11.99/mo |
| Ultra | Read & Write | 9 tools | 11 tools | $24.99/mo |
Pro and Ultra have the same MCP tools. Ultra has higher quotas (unlimited notes, 1500 STT min/mo, 300 uploads/day).
Authentication
Every request requires a Bearer token in the Authorization header. Tokens are generated in the web app settings.
- Regenerate: Settings > AI Agents > Regenerate (old token revoked instantly)
- Disable: Settings > AI Agents > Disable (token deleted)
- Rate limit: 5 requests/second
Transport
MCP Streamable HTTP (stateless). Each request is independent.
POST https://api.telldone.app/mcp/user/mcp
Authorization: Bearer <token>
Content-Type: application/json
Accept: application/json
Links
- App: app.telldone.app
- Website: telldone.app
- Docs: docs.telldone.app
- iOS App: App Store
Servidores relacionados
Kone.vc
patrocinadorMonetize your AI agent with contextual product recommendations
Rember
Create spaced repetition flashcards in Rember to remember anything you learn in your chats
Pleasanter MCP Server
An MCP server for interacting with the Pleasanter low-code/no-code business application platform.
Salesforce MCP
Interact with the Salesforce API using jsforce, requiring username and password for authentication.
Helios-9
Provides comprehensive project management context to AI agents using the Helios-9 API.
Google Calendar
Create and manage Google Calendar events with AI assistants.
Hyperpost
An AI-native publishing engine for persona-driven content creation and multi-platform publishing.
VAP media MCP
: MCP server for AI media generation (imagesflux, videosveo3.1, music suno v5, with deterministic cost control using reserve-burn-refund billing
Things MCP
Integrate with the Things 3 to-do app on macOS.
Brivvy MCP
Connects AI assistants to your Brivvy workspace so they can use your brand voices, templates, and glossary for on-brand content—hosted at mcp.brivvy.io.
Kash Business management
Kash.click management assistant. Connect your assistant to your business complete sales history, clients, payments, tax information, employees, points of sales.