Slack To Laptop

One long-lived local process, three hats: Slack @mention listener (Socket Mode), remote HTTP MCP server that Claude Code worktree jobs call to drive the native Slack stream, and SwiftBar menubar status.

threadTs is the correlation key: the worktree job only ever knows threadTs; this process maps it to the real Slack stream id. The map is snapshotted to ~/.cache/slack-to-laptop/registry.json, so restarting the bridge (deploys, crashes) doesn't interrupt running jobs: on boot, restored streams are force-rotated by the first keepalive tick — rotation doubles as recovery.

Slack app (one-time)

1. https://api.slack.com/apps → Create New App → From scratch.
2. Agents & AI Apps feature → toggle ON (grants assistant:write, required for streams + setStatus).
3. Socket Mode → ON → create app-level token with scope connections:write → that's appToken (xapp-…).
4. OAuth & Permissions → bot scopes: app_mentions:read, chat:write, assistant:write.
5. Event Subscriptions → subscribe to bot event app_mention.
6. Install to workspace → botToken (xoxb-…). Invite the bot to your channel: /invite @YourApp.

Note: Slack docs say setStatus is migrating from assistant:write to chat:write — both scopes above cover either.

Run

mkdir -p ~/.config/slack-trigger
cp config.example.json ~/.config/slack-trigger/config.json
# fill botToken + appToken
bun run server.ts

allowedUserIds (Slack user IDs): when non-empty, only those users can trigger jobs — anyone else gets a threaded "only can trigger me" reply. Empty = anyone in the channel.

With jobCommand: null, mentioning the bot runs a smoke demo: instant thinking checklist, two task cards ticking, "hi", stream closed. That validates the whole Slack side before wiring any jobs.

Wire real jobs

Set jobCommand in the config — a zsh command run per mention with env:

var	value
SLACK_THREAD_TS	correlation token — pass to every MCP tool call
SLACK_CHANNEL	channel id
SLACK_PROMPT	mention text, bot mention stripped
SLACK_EVENT_TS	unique per mention — use for the worktree name
SLACK_MCP_URL	http://127.0.0.1:8365/mcp

Example: "jobCommand": "/Users/you/projects/slack-to-laptop/scripts/launch-job.zsh" — see scripts/launch-job.zsh (machine-specific: tmux session + repo hardcoded). It spawns a worktree Claude with prompt /slack-ta [threadTs:$SLACK_THREAD_TS] $SLACK_PROMPT: the token travels inside the prompt, since the job's Claude only sees what the skill receives (see "Job-side skill" below).

Connect the worktree's Claude to the MCP (once, user scope):

claude mcp add --transport http --scope user slack-stream http://127.0.0.1:8365/mcp

MCP tools

All take threadTs (from SLACK_THREAD_TS):

• register_job({threadTs, cwd, tmuxPane?, pid?, branch?}) — call once at boot; where the session lives, for follow-up routing
• thinking_step({threadTs, title, status, id?, details?}) — checklist step; status ∈ pending|in_progress|complete|error; same id/title updates the step
• append_text({threadTs, markdown}) — prose in the progress message (important mid-course findings only)
• set_status({threadTs, text}) — grey "is …" line; "" clears
• finish({threadTs, markdown?}) — settle the progress message + post markdown as its own final-report reply (the user's one notification). Call exactly once, last (again after each follow-up).

Follow-ups

Mentioning the bot again in a job's thread does NOT spawn a second job: the bridge looks the thread up in ~/.cache/slack-to-laptop/jobs.json (written by register_job, survives finish for 7 days), verifies the session's tmux pane still sits in the job's worktree (pane ids get recycled — cwd is ground truth), and types [slack follow-up threadTs:…] <text> into that Claude session via tmux send-keys — mid-work it's a steering message, after finish a new turn with full context. A stream is reopened first if needed ("Reconnecting to session…"). If the pane is gone, it falls back to spawning a fresh job with a note. Only the typing is tmux-specific (src/inject.ts); finding the session is registration-based and generic.

Future idea (deliberately not built): worktree cleanup on job end conflicts with follow-ups — the kept-alive session is what makes them possible. Cleanest shape: an explicit "cleanup" follow-up telling the session itself to remove its worktree and exit.

A job that dies without finish gets swept: streams idle > staleStreamMinutes are stopped and cleared.

Slack hard-kills a stream ~5:00 after it opens, no matter what is appended (undocumented; measured — a true keepalive is impossible, even with changing content), and there is no way to re-stream onto an existing ts. Each job therefore gets ONE progress message: it streams natively while young (full card UI), is stopped cleanly at age ~3.5–4.5 min, and is edited in place via chat.update from then on (works on stopped streamed messages — measured). Conversion keeps the NATIVE cards: task_card is a real Block Kit block (changelog 2026-02-11), accepted by chat.update even on a stopped stream (measured) — the message re-renders from the replay log with identical card UI. No splits, no dup cards, no pings, no visual downgrade. The final report is the only other message — posted on finish(markdown), one notification, exactly when you want it.

Block-form quirks vs the chunk form (measured): task_card blocks REQUIRE status and reject "pending" (enum in_progress|complete|error) — pending steps simply aren't rendered yet; the plan block's title must be a plain string, not a plain_text object.

API gotchas (measured): chat.stopStream with markdown_text only works on a stream with NO chunks appended — streaming_mode_mismatch otherwise (the report is delivered as a chunkless stream + markdown-stop for the native agent look). Frozen in_progress cards render with a ⚠️ — finish completes them before its plain stop.

Job-side skill

Don't make each job improvise the streaming protocol — give your agent a skill (e.g. ~/.claude/skills/slack-ta/) that owns it. The launch command passes the correlation token inside the prompt (/slack-ta [threadTs:…] <task>); the skill should: extract threadTs and pass it to every slack-stream MCP call, open a thinking_step immediately, update the checklist at real milestones only, append_text for the final summary, and ALWAYS finish — also on failure. Two error rules worth copying: if the token is missing, do the work but skip streaming; if a call errors with "no live stream", the stream was swept — continue the work, stop streaming.

GET /healthz lists active streams.

Build your own

Want the same thing but different? The architecture is small enough to rebuild in an afternoon — here's the TL;DR to hand your agent (or read yourself).

The shape. One long-lived local process with three roles:

1. Listener — Slack Socket Mode (@slack/bolt), subscribed to app_mention. On mention: open the progress message instantly (so the user sees life before any job boots), then spawn the job however you like.
2. Bridge — a local HTTP MCP server (@modelcontextprotocol/sdk, stateless transport). The job's agent calls 5 tools: register_job, thinking_step, append_text, set_status, finish.
3. Status — optional (here: SwiftBar menubar). Any observer works; GET /healthz is the hook.

The one design trick: the job never holds Slack credentials or message ids. It only knows threadTs — a correlation token passed inside its prompt — and the bridge maps it to the real channel/message and owns the token. Any runner (tmux, container, CI, SSH) works as long as the token rides along and the runner can reach 127.0.0.1:8365.

The Slack rendering strategy (the hard-won part — all measured, none documented; see the section above for detail):

• Native streams (chat.startStream) look great but die ~5:00 in, no keepalive possible, no re-stream onto the same ts.
• chat.update works on stopped streamed messages, edits never ping.
• task_card is a real Block Kit block — chat.update can render the SAME native card UI forever. Quirks: status required, "pending" rejected, plan.title must be a plain string.
• ⇒ one message per job: stream while young, convert to edit-in-place at ~3.5 min, keep native cards throughout. Final report = separate message = the single notification.

State: one JSON map threadTs → {messageTs, mode, replayLog} snapshotted to disk — that's what makes bridge restarts invisible to running jobs (replay log re-renders the whole message). A second file maps threadTs → session location so re-mentions in a thread route INTO the running session (here: tmux send-keys, cwd-verified) instead of spawning a duplicate.

Reliability floor: dedupe redelivered Slack events (3s ack window); a stale sweep for jobs that die without finish; every Slack write has a fallback chain ending in plain chat.postMessage.

Adaptation points — each is one file here: how jobs launch (scripts/launch-job.zsh — swap for docker/ssh/whatever), how follow-ups reach a session (src/inject.ts — the only tmux-specific code), what the agent streams (your job-side skill/prompt: milestones as thinking_step, summary in finish(markdown), ALWAYS finish — also on failure).

SwiftBar

cp swiftbar/slack-to-laptop.sh ~/Library/Application\ Support/SwiftBar/Plugins/  # or your plugin dir
chmod +x .../slack-to-laptop.sh

Streamable plugin: SwiftBar owns the process lifecycle; menubar shows 🛰️ + active stream count. Don't also run bun run server.ts manually (port collision). Test from a terminal first: ./swiftbar/slack-to-laptop.sh — you should see blocks starting with ~~~. Logs: ~/.cache/slack-to-laptop/server.log (written by the server itself — NEVER add a stderr redirect to the plugin script: closing SwiftBar's stderr pipe makes it spin at 100%+ CPU).

SwiftBar does NOT respawn the process if it dies. To restart the bridge: open -g "swiftbar://refreshplugin?name=slack-to-laptop" (or SwiftBar menu → plugin → Refresh). If the 🛰️ icon is missing but the process runs, check defaults read com.ameba.SwiftBar for "NSStatusItem VisibleCC slack-to-laptop.sh" = 0 and write it back to -bool true.