
If Part 1 was the theory, Part 2 is the lab. You’ve seen why MCP matters — now let’s make your AI operate inside your tools. This hands-on guide shows how to connect Notion, ClickUp, and Google Sheets with MCP so tasks move, notes brief, and reports build themselves.
Table of Contents
- 1) Prepare Your Environment (Local vs Remote MCP)
- 2) Connect Notion with MCP (DB search & doc briefing)
- 3) Connect ClickUp with MCP (status updates & team alerts)
- 4) Connect Google Sheets with MCP (live reports)
- 5) Troubleshooting — Quick Checklist & Security Tips
1) Prepare Your Environment (Local vs Remote MCP)
Local MCP vs Remote MCP — choose depending on how you want to share and scale:
Mode | Best For | Pros | Cons |
---|---|---|---|
Local MCP | Individuals, prototyping | Quick setup, full control on your machine | Tied to device, harder to share with team |
Remote MCP | Teams, production | Cloud access, collaboration, policy enforcement | Requires org setup & secret management |
[Your Chat/AI] │ ├── Local MCP (on your laptop) │ ├─ Notion Tool (read-only default) │ ├─ ClickUp Tool (limited write: status/assignee) │ └─ Sheets Tool (Log sheet only write) │ └── Remote MCP (cloud) ├─ Org-wide policies (scopes, audit, rotation) ├─ Secrets vault └─ Team-wide access & SLAs
Minimal checklist before you start:
- Choose Local or Remote MCP.
- Generate API tokens/credentials for Notion, ClickUp, Google.
- Store secrets in a vault (not in code); apply least privilege.
- Whitelist only the resources you want readable vs writable.
- Pick Local vs Remote MCP (who needs access, how will you share?).
- Create per-tool credentials (Notion/ClickUp/Google). Use least privilege.
- Keep tokens in a vault; never paste them in prompts.
- Whitelist DB/List/Sheet IDs instead of entire workspaces.
2) Connect Notion with MCP (DB search & doc briefing)
One-line takeaway: Turn scattered Notion pages into a meeting-ready brief in one request.
Goal: Let AI search a Notion database, pull pages, and draft a meeting summary.
What you need: Notion integration (internal), a database (e.g., “Meetings” or “Projects”), and MCP-connected AI chat.
- Create a Notion integration → Settings & Members → Integrations → New integration → copy the token.
- Share your database with the integration → open DB → Share → invite integration.
- Register the Notion tool in your MCP config (token, allowed DB IDs, read/write scopes).
- Ask AI:
- “Search DB ‘Meetings’ for pages tagged ‘Quarterly Review’ in the last 30 days.”
- “Fetch the latest 5 pages and summarize key decisions and owners.”
{ "tools": { "notion": { "type": "notion", "config": { "token_env": "NOTION_TOKEN", "allow": { "database_ids": ["", " "], "page_read": true, "page_write": false // start read-only } } } } }
Note: field names vary per runtime, but principles stay: store tokens in a vault, whitelist DB IDs, default to read-only.
Plan the steps, then run via Notion tool: 1) Search database "" for pages tagged "Quarterly Review" updated in the last 30 days. 2) Fetch the latest 5 pages (title, last_edited_time, owners, decisions). 3) Draft a 1-page meeting brief: - Objectives - Key decisions (with page links) - Open risks (with owners) 4) Show the plan before execution. No page writes, read-only.
Practical scenario: Before a leadership sync, AI compiles objectives, decisions, and action items into one brief with links to source pages.
Guardrail: Default to read-only; enable write only if auto-creating summary pages.
3) Connect ClickUp with MCP (status updates & team alerts)
One-line takeaway: Daily auto-triage of stale tasks with bulk updates and Slack digests.
Goal: Review in-progress tasks, bulk-update statuses, and notify the team.
What you need: ClickUp token, target Space/Folder/List IDs, and a Slack channel.
- Create a token → ClickUp Settings → Apps → generate token.
- Map structure: Space → Folder → List → Task (identify MCP scope).
- Register ClickUp tool in MCP (token, allowed Lists, allowed fields).
- Ask AI:
- “List tasks ‘In Progress’ with no updates in 7 days; propose next status and owner.”
- “Bulk-move matching tasks to ‘Blocked’ and @mention owners.”
- Optional: add Slack tool; “Post a summary of today’s changes to #daily-ops.”
{ "tools": { "clickup": { "type": "clickup", "config": { "token_env": "CLICKUP_TOKEN", "allow": { "list_ids": ["", " "], "write_fields": ["status", "assignees", "due_date"], "write_enabled": false // start dry-run only } } } } }
Stage 1 (Dry-run): - List tasks in "In Progress" with no updates in 7 days from. - Suggest next status and owner for each. - Show summary table. No writes. Stage 2 (Approve): - After "apply changes", update only: • status → "Blocked" • assignees → preserved - Post Slack summary to "#daily-ops". - Log writes (task_id, old→new, timestamp) to audit sheet.
Practical scenario: Each morning, AI audits stale tasks, flags risks, proposes next steps, applies updates, and posts to Slack.
Guardrail: Always start in dry-run. Restrict write to certain Lists and fields.
4) Connect Google Sheets with MCP (live reports)
One-line takeaway: Automated 9am metrics with live charts and 3-bullet insights.
Goal: Query live data, generate metrics/charts, and share a short report.
What you need: Google Cloud project (service account or OAuth), target Sheet shared with the account, read/write scopes.
- Enable Sheets API → create service account → store key securely.
- Share the Sheet with the service account (viewer/editor).
- Register the Sheets tool in MCP (credential path, allowed Sheet IDs, scopes).
- Ask AI:
- “Read Report!A1:G, compute WoW trend, and draft 3-bullet insights.”
- “Append a row to Log!A:D with today’s KPIs and timestamp.”
- Optional: send chart + summary via Slack/email.
{ "tools": { "sheets": { "type": "google_sheets", "config": { "credential_env": "GOOGLE_SA_KEY", "allow": { "spreadsheet_ids": [""], "read_ranges": ["Report!A1:G", "Summary!A1:D"], "write_ranges": ["Log!A:D"], "write_enabled": true } } } } }
1) Read Report!A1:G, compute WoW changes for Sessions, CTR, Conversions. 2) Flag anomalies (drop >15%). 3) Append row to Log!A:D [timestamp, Sessions, CTR, Conversions]. 4) Draft a 3-bullet executive insight. 5) (Optional) Post chart + insight to Slack #kpi-daily.
Practical scenario: At 9am, AI reads KPIs, flags anomalies, publishes a chart with analysis.
Guardrail: Default read-mostly; allow writes only to Log sheet. Scope by Sheet ID, not domain-wide.
5) Troubleshooting — Quick Checklist & Security Tips
Quick Checklist (TL;DR)
- 🔐 Access: Does the integration user have DB/List/Sheet access?
- 🧭 Scopes: Read vs Write scoped correctly? Start read-only.
- 🧪 Dry-run: Preview changes before write.
- 🧾 Audit: Log who/when/what for all writes.
- 🧱 Granularity: Whitelist only needed IDs, not whole workspaces.
- 🔄 Tokens: Rotate quarterly; keep in a vault.
- 🚦 Rate limits: Batch ops; backoff on throttling.
- 🔐 Ensure integration user has DB/List/Sheet access.
- 🧭 Start read-only → expand write only when needed.
- 🧪 Run dry-tests before applying bulk writes.
- 🧾 Log all writes (who/what/when).
- 🧱 Whitelist resource IDs, not full workspaces.
- 🔄 Rotate tokens every quarter, store in vault.
- 🚦 Avoid throttling by batching ops + backoff.
Deeper tips
- Permissions mismatch: Most failures are sharing issues — fix access first, then retry.
- Plan disclosure: Ask AI to explain the plan and list target resources before execution.
- PII/Secrets: Redact prompts/responses; never echo secrets back to chat.
Explore Part 3 → MCP vs Zapier vs n8n (Automation Scenarios & Comparisons)