inbox-to-action

Published on PyPI and listed on the Official MCP Registry (io.github.tarunlnmiit/inbox-to-action), Glama (deployable release, Quality A), and Smithery (MCPB bundle). Registry manifests (server.json, glama.json) ship in the repo.

One command. Your inbox triaged, summarized, drafted, and turned into tasks — in a single agentic pass.

Install

pip install inbox-to-action          # or: pipx install inbox-to-action
uvx inbox-to-action run --mock       # zero-install trial (uv)
pip install 'inbox-to-action[mcp]'   # + MCP server for Claude Code
docker run --rm ghcr.io/tarunlnmiit/inbox-to-action   # MCP server (stdio)

Try it with zero setup: inbox-to-action run --mock (bundled sample inbox).

📖 Full documentation → docs/ — install · providers · Gmail OAuth · multi-account · integrations · MCP & Skill · config · troubleshooting · testing checklist. Quick version: SETUP.md.

Why this exists

Most people process their inbox with four separate tools: an email client to read, a task manager to capture to-dos, a calendar to block time, and (increasingly) an AI summarizer to make sense of long threads. Every message gets handled four times.

inbox-to-action collapses all four into one agentic pass. Run one command and get a unified triage report, drafted replies saved to Gmail, and extracted tasks — without ever leaving the terminal, and without ever sending an email automatically.

🔒 Drafts only — never sends

This tool cannot send email. It requests only the Gmail readonly + compose scopes; there is no send scope and no send API call anywhere in the codebase (enforced by a test). Replies are saved as Gmail drafts for you to review and send.

Email bodies flow into the LLM prompt, so a hostile email could try to steer its own classification or a drafted reply (prompt injection). Because every draft is saved for human review and nothing is ever sent automatically, the worst case is a draft you choose not to send. See SECURITY.md.

🌐 What leaves your machine

inbox-to-action reads your email. Where your email content goes for classification depends on the LLM provider you pick — and the default (openrouter) is a cloud provider, so an out-of-the-box run sends your subjects + bodies to a third party.

Want privacy? Use ollama (local) or claude (keyless) so nothing is transmitted to a third party. --telegram / --todoist also push subjects/tasks off-box (opt-in). Full breakdown → PRIVACY.md.

Note: triage-report.md and tasks.md are written to your working directory and contain private email content. If you run inside a git repo, add them to .gitignore.

What it does

1. Fetches unread email from Gmail (last 24h by default).
2. Classifies each into action_needed · fyi · newsletter · noise.
3. Summarizes long threads (>500 words) into two lines.
4. Extracts tasks with deadlines → local tasks.md (optional Todoist via --todoist).
5. Drafts replies for action_needed mail → saved as Gmail drafts.
6. Flags emails that need a calendar block.

Final output: a single triage-report.md with a section per category, drafted-reply previews, a tasks summary, and a calendar list.

Architecture — the agent loop

The model's own classification of each email drives which tools fire next — the pipeline is not hardcoded. The same tool functions back the CLI agent and the MCP server.

flowchart TD
  CLI[main.py · typer] --> AGENT[agent.py · agentic loop]
  AGENT -->|model picks tools per email| T1[classify_email]
  AGENT --> T2[summarize_thread]
  AGENT --> T3[extract_tasks]
  AGENT --> T4[draft_reply → Gmail draft]
  AGENT --> T5[flag_for_calendar]
  T1 & T2 & T3 & T4 & T5 --> LLM[llm_client.py · pluggable providers]
  LLM --> P1[OpenRouter / Ollama / NIM / OpenAI<br/>OpenAI-compatible HTTP]
  LLM --> P2[Anthropic · official SDK · keyless via ant auth login]
  AGENT --> REPORT[report.py → triage-report.md]

fetch → for each email:  classify ─┬─ action_needed → extract_tasks + draft_reply + flag_calendar
                                   ├─ fyi / newsletter / noise → record only
                                   └─ (long thread) → summarize
                          → render triage-report.md

Quick start (2 minutes)

git clone https://github.com/tarunlnmiit/inbox-to-action.git && cd inbox-to-action
python3 -m venv .venv && source .venv/bin/activate
pip install -e '.[mcp]'        # installs the `inbox-to-action` command
cp .env.example .env

This installs an inbox-to-action console command (and the python -m inbox_to_action.mcp_server entry point used by Claude Code / Glama).

Free-first: run end-to-end on zero spend

Pick whichever keyless/free path you like — all run the full pipeline at no cost:

Option A — claude CLI (keyless, fastest; uses your Claude Code login):

PROVIDER=claude inbox-to-action run --mock     # no API key; needs `claude` on PATH

Option B — Ollama (truly keyless, fully local):

ollama serve            # in another terminal
ollama pull llama3.1
PROVIDER=ollama inbox-to-action run --mock     # uses bundled sample inbox

Option C — OpenRouter free model (free signup key):

# put OPENROUTER_API_KEY in .env (free models, $0 spend)
inbox-to-action run --mock                      # default PROVIDER=openrouter

Option D — inside Claude Code (keyless, Claude Code is the LLM): see below.

--mock uses the bundled sample inbox so you can see a full report with zero Gmail setup. Drop --mock once you've authorized Gmail. Free OpenRouter models are often rate-limited; the client auto-rotates a fallback list and retries with backoff.

Real inbox

# 1. Create OAuth credentials in Google Cloud Console (Desktop app),
#    download client_secret.json into the project, then:
inbox-to-action auth                 # one-time consent (read + compose only)
inbox-to-action run --since 24h --no-drafts   # safe first pass: report only, no writes
inbox-to-action run --since 24h      # triage the last day (creates Gmail drafts)
inbox-to-action run --since 3d --max 40 --todoist

• --no-drafts — classify, summarize, extract tasks, write the report, but create no Gmail drafts. Recommended for a first run.
• --max N — cap emails per account (default 25) to bound cost/volume.
• Automated no-reply senders (security alerts, notifications) never get a drafted reply — the report notes them instead.

Telegram summary (--telegram)

Push a concise summary to your phone after each run — counts, action-needed subjects (with draft-ready status), extracted tasks, and a link to your Gmail Drafts.

# 1. In Telegram, message @BotFather → /newbot → copy the bot token.
# 2. Message your new bot once (say "hi"), then open:
#    https://api.telegram.org/bot<token>/getUpdates  → copy "chat":{"id": ...}.
# 3. Put both in .env:
#    TELEGRAM_BOT_TOKEN=...   TELEGRAM_CHAT_ID=...
inbox-to-action run --since 24h --telegram

Off by default (opt-in flag). A send failure never breaks the run. Privacy: this sends email subjects + extracted tasks to Telegram's servers (into your own chat). It's notification only — it never sends email.

Multiple accounts (Gmail + Google Workspace)

Declare accounts in config.json — one merged report, each email tagged with its account. Personal Gmail and Workspace both use the Gmail path (Workspace may need your admin to allow the OAuth app).

{
  "accounts": [
    { "id": "personal", "kind": "gmail", "label": "Personal Gmail" },
    { "id": "work",     "kind": "gmail", "label": "Workspace" }
  ]
}

inbox-to-action auth --account personal   # authorize each account once
inbox-to-action auth --account work
inbox-to-action run --since 24h           # fetches + triages across all accounts