Follow-Through
Automatically creates a Linear ticket for every extracted commitment, checks ticket status for evidence of completion, updates statuses, and escalates overdue commitments by adding a manager watcher and a contextual comment.
Searches Slack channels for evidence of commitment completion (messages from the owner with matching keywords and completion signals) and sends direct-message nudges to commitment owners as part of the escalation ladder.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Follow-Throughextract commitments from this meeting transcript and track them"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Follow-Through
The MCP agent that remembers what everyone promised — so nothing quietly dies.
Follow-Through is a TypeScript Model Context Protocol (MCP) server built on NitroStack. It listens to meeting transcripts, extracts every spoken commitment (who promised what, to whom, by when, and with what confidence), persists it durably, and then keeps working autonomously: it polls Slack, email, and Linear for real evidence of completion, sends escalating nudges when deadlines slip, and escalates to a manager's inbox when a commitment goes silent — all without a human having to re-prompt it.
For a demo, a compressed virtual clock (simulate_days_passing) makes a full
week of follow-up observable in seconds, and a companion widget renders the
live commitment board.
Why this exists
Most action items from meetings never make it into a tracker. They live in a transcript nobody re-reads, get half-remembered, and quietly expire. Follow-Through closes that loop in three moves:
Capture — the moment a promise is spoken, it becomes a durable record with an auto-created Linear ticket.
Verify — instead of nagging blindly, the agent checks Slack and email for evidence that the work actually got done.
Escalate gracefully — if there's no evidence and no response, nudges get more specific, and a human manager is looped in with full context.
Related MCP server: Docket MCP Server
Key features
Feature | What it does |
Commitment extraction | Parses transcripts into structured commitments via a pluggable LLM (Anthropic, OpenRouter) or a fully offline deterministic parser — same output shape either way. |
Confidence triage | Each commitment is graded |
Durable store | Pure-JS JSON-file persistence (atomic writes, serverless-safe) with a virtual clock, so the whole lifecycle can be simulated deterministically. |
Evidence-based "done" | Completion is decided by real signal — a Slack message or email from the owner with matching keywords and a completion signal — not by assumption. |
Escalation ladder |
|
Linear integration | Every commitment gets a ticket (LIN-48x); escalated tickets gain a manager watcher and a contextual comment. |
Live dashboard widget | A Next.js widget auto-attached to |
Demo controls |
|
Zero-cost default | Runs fully offline with no API key; free OpenRouter models are optional. |
How it works
┌────────────────────────────────────────────────────────┐
transcript │ App │
─────────────► │ ingestion ──► store ──► evidence ──► nudge ──► linear │
│ ▲ │
│ │ scheduler (poll loop / clock) │
│ widget ◄───────┴── query_commitments │
└────────────────────────────────────────────────────────┘Modules
Module | Responsibility |
| Extract structured commitments from transcripts (LLM or offline). |
| JSON-file persistence: commitments, evidence/nudge logs, escalation state, virtual clock. |
| Search Slack/email for completion signal (real providers, with fixture fallback in demo mode) and score it against the commitment. |
| Compose and send reminders across Slack/email with tone control (real delivery, fixture/log in demo mode). |
| Ticket lifecycle: create, status, escalate (with manager watcher + comment). |
| The autonomous loop. Polls due commitments, checks evidence, advances the state machine. |
The decision state machine
For each due, non-aspirational commitment, the scheduler runs every poll:
due (+ grace) +3d (committed) +6d (committed)
open ───────────────────► nudged_1 ─────────────► nudged_2 ─────────────► escalated
gentle nudge specific nudge manager + watcherAt every step it first checks evidence (Slack/email) and ticket status
(Linear Done) — proof beats nagging. Nudges only happen when there is
neither evidence nor a completed ticket.
Confidence tiers and cadence
Tier | Example | Grace for nudge 1 | nudge 2 | escalate |
| "I will ship the report by Friday" | at due date (0d) | +3d | +6d |
| "I'll try to get it done by Friday" | +2d | +5d | +10d |
| "We should probably track error budgets" | never chased | — | — |
Evidence scoring
scoreEvidence() in src/common/matching.ts combines three signals:
Recall — what fraction of the commitment's key terms appear in the message
Completion signals — words like sent, published, shipped, delivered, merged
Author match — the message came from the commitment owner
A score ≥ 0.6 marks the commitment done. Keyword-only mentions cap at
0.55 — deliberately below the bar, because a false "done" is worse than a
false nudge.
Technology stack
Runtime: Node.js ≥ 20 (ESM, TypeScript strict mode)
Framework: NitroStack (
@nitrostack/core) — decorator-based modules, DI, MCP serverPersistence: Pure-JS JSON-file store (
data/follow-through.json, atomic writes) — zero native dependencies, deploy-safe on any base imageValidation: Zod
LLM:
fetch-based calls (no heavy SDK) — Anthropic Messages API or OpenRouter chat-completionsWidgets: Next.js 14 + React 18 (
@nitrostack/widgets)
Project structure
src/
app.module.ts # root module — wires all six modules
common/
types.ts # Commitment, Person, Ticket, evidence/nudge types
dates.ts # date math + virtual-today helpers
matching.ts # evidence scoring + thresholds
modules/
ingestion/ # extract_commitments + sample transcript fixture
store/ # JSON-file store + virtual clock + query/upsert/promote
evidence/ # search_slack_evidence / search_email_evidence
nudge/ # send_nudge
linear/ # linear_create_ticket / get_status / update_status / escalate
scheduler/ # simulate_days_passing / reset_demo + poll loop
providers/
slack.ts # real Slack evidence search + DM nudges (Slack Web API)
email.ts # real SMTP send + IMAP evidence search
linear.ts # real Linear GraphQL client
widgets/app/commitment-dashboard/ # the live dashboard widget (Next.js)
scripts/
e2e-smoke.mts # full-lifecycle regression test (30+ asserts)
extract-sample.mts # one-liner demo: sample transcript → extract_commitments
check-state.mts # dump live server truth (commitments + ticket statuses)
providers-check.mts # which real providers/LLM keys are configured
live-check.mts # live create/read/update against real Linear + Slack/email searchGetting started
Prerequisites
Node.js ≥ 20 (developed on 24.15.0)
npm
Install
npm install
npm run buildThe build compiles TypeScript to dist/ and bundles the widget to
src/widgets/out/.
Configuration
Copy .env.example to .env. Everything has sane defaults; no key is required.
Variable | Default | Purpose |
|
|
|
| — | Enables Claude-based extraction (paid) |
|
| Claude model |
| — | Enables free-tier OpenRouter extraction |
|
| Free OpenRouter model |
|
| Real-world poll cadence (production) |
|
| Writable volume for the JSON store (falls back to temp, then in-memory) |
| — | Enables real Slack evidence search + DM nudges |
| — | Comma-separated channels to search for evidence |
| — | Enables real outbound nudges by email |
| — | Enables real IMAP evidence search |
| — | Enables real Linear ticket lifecycle |
| — | Linear team for ticket creation (auto-detected if omitted) |
Provider resolution (auto): uses Anthropic if its key is set, else
OpenRouter if its key is set, else the offline deterministic extractor.
Any LLM failure falls back to the offline extractor — the demo never breaks.
Demo vs. real mode: when none of SLACK_BOT_TOKEN, EMAIL_IMAP_*, or
LINEAR_API_KEY are set, the server runs in demo mode and all Slack/email/
Linear traffic is fixture-based. Configure any subset and only those providers
go real — the rest keep their fixtures. Run npx tsx scripts/providers-check.mts
to see which mode you're in.
No key? No problem. The deterministic extractor produces the same structured output from the same tool schema with zero network and zero cost.
Running
Development (recommended for demoing)
npm run devMCP server runs over stdio (wait for a client, see Connect a client)
Widget dev server runs on http://localhost:3001 with hot reload (route:
http://localhost:3001/commitment-dashboard)
Production
npm run build
npm startBoots in dual mode — stdio and HTTP at http://localhost:3000/mcp.
Demo walkthrough
The sample transcript (mtg_ops_standup) contains four commitments designed
to exercise every path: a completion, a slacker, a hedged promise, and an
aspirational wish.
# 0. Clean slate (virtual "today" = real today, e.g. 2026-07-31)
reset_demo
# 1. Extract commitments from the sample transcript → 4 commitments + 4 Linear tickets
get_sample_transcript
extract_commitments { transcript_text, participants, meeting_date }
# 2. Fast-forward 3 days (→ Aug 3, the first due date)
simulate_days_passing { days: 3 }
# Priya → done_evidence (Slack + email show the report was sent)
# Marcus → nudge_1 (gentle nudge, no evidence yet)
# 3. Fast-forward 3 days (→ Aug 6)
simulate_days_passing { days: 3 }
# Marcus → nudge_2 (more specific nudge)
# 4. Fast-forward 3 days (→ Aug 9)
simulate_days_passing { days: 3 }
# Marcus → escalated (ticket watcher: raj.patel@company.com + context comment)
# Aisha → nudge_1 (hedged — grace period meant she wasn't chased early)
# Tom → open, untouched (aspirational — never auto-chased)
# 5. Inspect the final board
query_commitments
# 6. Prove the escalation stuck to the ticket
linear_get_status { ticket_id: "LIN-482" } # → Escalated, watchers: [...]For a browser visual, open the dashboard widget (see below) — it reflects the same board.
Tools
All 14 tools registered on the follow-through MCP server:
Tool | Module | Purpose |
| ingestion | Ready-to-use demo transcript + roster |
| ingestion | Parse transcript → commitments, records, tickets |
| store | Insert/update a commitment record |
| store | Query the board (status filters; widget-attached) |
| store | Raise a commitment's confidence tier |
| evidence | Search Slack for completion signal (real or fixtures) |
| evidence | Search email for completion signal (real or fixtures) |
| nudge | Send a reminder (tone, channel, message) |
| linear | Create a Linear ticket |
| linear | Read ticket status, watchers, escalation comment |
| linear | Change ticket status |
| linear | Escalate a ticket to a manager |
| scheduler | Advance virtual clock + run one poll |
| scheduler | Wipe state, reset clock |
Widget dashboard
query_commitments is auto-attached to a Next.js widget
(ui://widget/next-commitment-dashboard.html). Inside an MCP host it renders a
theme-aware board: owner, commitment, due date, confidence, status badge,
evidence trail, and nudge count.
Standalone (no host injecting data) the page shows only a loading shell — the data is injected by the host when the tool runs.
Testing
npm run build
npx tsx scripts/e2e-smoke.mtsDrives the real server over the MCP stdio protocol and asserts 30+ invariants:
extraction shape, confidence tiers, due-date resolution, nudge timing, hedged
grace, aspirational immunity, evidence thresholds, escalation watcher, and
manual nudges. Ends with ALL CHECKS PASSED.
Verify what the agent reports (before the demo, and anytime a tool call fails)
If a client like Claude.ai ever reports a connector error mid-demo, never assume the answer that followed came from the server — re-run the tools live and compare:
npm run build
npx tsx scripts/check-state.mtsThis dumps the server's actual current commitments and Linear ticket statuses
(each ticket includes as_of, the server-side date the status was read at), so
anything the agent quoted can be checked against ground truth. Real tool
responses always carry server data (updated_at, as_of, ticket ids); anything
that doesn't match a fresh run is client-side reconstruction, not a result.
Demo etiquette: if a tool call visibly fails, say "let me retry that" and call it again instead of continuing — a visibly retried tool beats a confidently wrong number. Connector errors ("Connector search is off", "Unable to reach …") are almost always Claude.ai's connector settings: open Settings → Connectors, confirm the FollowThrough connector is enabled/approved, and re-approve it for the current conversation (approval is per-chat, so a new chat needs it again).
Simulation semantics
simulate_days_passing takes a single days number and advances the virtual
clock by exactly that many days in one call (then runs one scheduler poll). So
{ days: 9 } jumps straight to due+9 in a single step — it is not three 3-day
calls. The demo shows a cleaner narrative with separate calls (3 → 3 → 3), which
also makes each nudge/escalation stage observable as it happens, but the tool
never requires them.
Connect a client
Point any MCP client (Claude Desktop, Cursor, etc.) at the built server:
{
"mcpServers": {
"follow-through": {
"command": "node",
"args": ["<path-to>/dist/index.js"],
"cwd": "<path-to>"
}
}
}Or hit the HTTP endpoint in dual/production mode: http://localhost:3000/mcp.
The CLI can also wire up Cursor automatically: npx nitrostack-cli cursor.
Production considerations
Real integrations, optional. Slack (
src/providers/slack.ts), email (src/providers/email.ts), and Linear (src/providers/linear.ts) are plain env-driven clients. Without keys they fall back to the deterministic fixtures, so the demo and the production path are the same code.Slack requires a bot token with
channels:read,groups:read,channels:history,groups:history,im:history,users:read,users:read.email,chat:write. The*:readscopes resolve channel names inSLACK_EVIDENCE_CHANNELSto ids (names or ids both accepted); the bot must be added to every channel it searches. Nudges DM the commitment owner.Email uses SMTP (
EMAIL_SMTP_*) for outbound nudges and IMAP (EMAIL_IMAP_*) to search mail for evidence, parsed withmailparser.Linear uses the GraphQL API (
LINEAR_API_KEY); escalations add the manager as a ticket subscriber plus a contextual comment.
Real cadence. Set
SCHEDULER_INTERVAL_MSto the desired poll rate and removesimulate_days_passing/reset_demofrom the tool surface if you don't want them exposed.LLM cost. Extraction is the only LLM call. It runs once per transcript; the polling/nudge/escalation machinery is pure code. Use OpenRouter
:freemodels or the offline extractor to keep cost at $0.Transport. Production boots in dual mode (stdio + HTTP). OAuth logs at startup are framework noise unless you configure an authorization server.
Troubleshooting
Symptom | Fix |
| A stale server is still running — kill it (netstat/ |
Widget missing on startup | Run |
Demo stuck on old dates |
|
| Expected on serverless hosts — the store auto-falls back to the OS temp dir, then in-memory only (look for |
Slack logs | The bot token lacks |
Linear logs | The |
| The LLM call failed or no key is set — check |
| The dashboard lives at |
License
MIT — see the repository root. Built for demonstration on the NitroStack MCP framework.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityCmaintenanceA persistent state machine and notification system for AI agents to manage complex, multi-step workflows via the Model Context Protocol, preventing context drift by maintaining structured checklists and sending desktop alerts.Last updated14272Apache 2.0
- FlicenseDqualityCmaintenanceEnables extracting action items from meeting transcripts and managing them in Notion, with duplicate detection and human review.Last updated3
- Alicense-qualityBmaintenanceEnables AI agents to capture, manage, and retrieve todos with due dates and provenance, while automatically escalating reminders until tasks are completed.Last updatedMIT
- Flicense-qualityCmaintenanceEnables product managers to analyze meeting transcripts, create tasks in Linear with deduplication, post messages and DMs on Slack, and generate weekly digests, all through natural language via MCP.Last updated
Related MCP Connectors
Your AI copilot for customer onboarding — projects, KPIs, tasks, and safe writes.
An AI-first personal CRM you run in natural language: contacts, reminders, notes, and more.
Manage projects, tasks, time tracking, and team collaboration through natural language.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ionfwsrijan/FollowThrough'
If you have feedback or need assistance with the MCP directory API, please join our Discord server