Give your support agent a Google Sheet to read
Support agents answer faster when the facts are one lookup away. Keep orders, refund policies, FAQ, and account tiers in a Google Sheet and PasteSheet publishes it as an MCP server your agent reads on every ticket — accurate and read-only, so it can quote a policy or check an order but never edit the record.
Last updated
Key facts
-
PasteSheet's MCP server exposes three tools —
list_tabs,get_schemaandquery_rows— and is read-only by design: an agent can query your sheet but can never modify it. - MCP is an open protocol built on JSON-RPC 2.0. A server exposes Resources, Prompts and Tools to any MCP client — Claude, Cursor, ChatGPT, VS Code and Windsurf all speak it. source
- Google's hosted Workspace MCP servers cover Gmail, Drive, Calendar, Chat and the People API — not Sheets. Its managed Google Cloud MCP servers do not cover Sheets either. source
- Google does publish an open-source Workspace MCP server (a Gemini CLI extension) that includes Sheets — but you run it yourself, and it still needs a Google Cloud project and OAuth credentials. There is no hosted, zero-setup Google Sheets MCP server from Google. source
-
Customer data need not be public: private endpoints and API keys start on Starter ($9/mo), and the agent then sends an
Authorization: Bearerkey to read the lookup tabs.
A lookup table your agent can trust
When a ticket comes in, a support agent — human or AI — needs the customer's order, the relevant policy, and the account tier, fast. Keep those in a Google Sheet and PasteSheet exposes them as an MCP server the agent queries mid-conversation: look up an order by id, match a refund policy, or check whether a plan includes a feature.
Because the tools are read-only, this is safe to put in an automated support loop. The agent reads every row it needs to answer accurately, but it cannot mark an order refunded, bump a tier, or rewrite a policy — your records stay exactly as your team left them.
What lives in the tabs
One tab per lookup, all reachable from the same endpoint:
- Orders — id, status, items, and ship date the agent looks up per ticket.
- Policies — refund windows, warranty terms, and SLAs to quote verbatim.
- FAQ — canned answers to the questions that fill your inbox.
- Account tiers — plan, limits, and entitlements per customer.
Connect the support sheet
Each endpoint has its own MCP URL. Copy it from the Connect via MCP panel and add it as a custom connector in your support agent's runtime:
{
"mcpServers": {
"pastesheet": {
"url": "https://pastesheet.com/mcp/sheets/your-endpoint-id"
}
}
}Read-only, so it cannot change a record
Because the endpoint is read-only by design, it is safe to expose publicly or hand to a teammate: consumers can read and query the data but can never change the sheet. And there is no Google Cloud project, OAuth screen, or service account to set up — you paste a share URL and get a live API.
What it costs
Starter
For indie makers shipping a real app.
- Endpoints
- 10
- Requests / mo
- 50,000
- Row cap
- 5,000
- MCP for AI agents
- Private endpoints & keys
- Full-text search
MCP is included on the Free plan. Connect any public endpoint over MCP with no Google Cloud project and no credit card. Private endpoints and the account-wide workspace server need a paid plan (from Starter ($9/mo)) for the keys and OAuth they authenticate with.
Pro adds full-text search and aggregation (count, sum, avg, group_by) that your AI agent can call through query_rows.
Frequently asked questions
Can the support agent change an order or account tier?
No. The connector is read-only. The agent can look up an order, quote a policy, or check a tier, but it cannot mark anything refunded, edit a record, or delete a row.
How does the agent find the right customer?
With query_rows — an exact filter on an order id or email, a contains match on a name, or full-text search across the tab. It pulls just the matching row rather than the whole sheet.
Is customer data exposed publicly?
Not if you make the endpoint private on a paid plan. It then requires a bearer key, which the agent sends as an Authorization header; the raw sheet is never public.
Which agents can use the lookup?
Any MCP-compatible client — Claude, Cursor, Claude Code, ChatGPT via the workspace server, or a custom support bot. The same endpoint also works over plain REST for frameworks without MCP.
Sources
- Model Context Protocol specification — Model Context Protocol
- Configure the Google Workspace MCP servers — Google
- google/mcp — Google's open-source MCP servers — Google
- Model Context Protocol (MCP) — OpenAI
Related use cases
A Google Sheets Data Source for AI Agents
Give any AI agent read-only access to a Google Sheet over MCP. It can list tabs, read the schema, and query rows in plain English — no glue code, no backend.
A Chatbot Knowledge Base in Google Sheets
Keep your chatbot's Q&A and product facts in a Google Sheet it queries over MCP or REST — accurate answers from live rows, with no vector store to run.
A RAG Data Source From Google Sheets
Skip the vector store for small, structured corpora: your agent retrieves rows from a Google Sheet with query_rows filters and full-text search over MCP.
Power an FAQ Page from a Google Sheet
Build a searchable FAQ or help page from a Google Sheet — one row per question and answer. Full-text search over questions via a live, read-only JSON API.
Turn your sheet into an API in minutes
Paste a Google Sheet URL and get a live REST API and MCP server — no backend, no code, free to start.