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Summary
Drive Coda (docs + tables + formulas) from any AI agent: docs, tables, rows, columns, formulas, packs, controls. 13 tools, Bearer token auth.
Try asking
Example prompts for Coda
Click any prompt to copy it. Paste into Claude, ChatGPT, Cursor, Gemini, Copilot or OpenClaw to run it against this connector.
Claude is AI and can make mistakes. Please double-check responses.
💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → Coda, paste your credentials, mint an MCP API key — done. No Docker, no
git clone, no local server.
Coda + Gemini
Drive Coda (docs + tables + formulas) from any AI agent: docs, tables, rows, columns, formulas, packs, controls. 13 tools, Bearer token auth.
Prerequisites
See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:
CODA_API_TOKEN
Step 1 — Get credentials
Setup:
- Sign in to https://coda.io → top-right avatar → Account → API settings → Generate API token.
- Name the token. Copy it. Set
CODA_API_TOKEN.
Authentication: Authorization: Bearer ${CODA_API_TOKEN}.
Resource hierarchy: Doc → Section (Page) → Table → Row → Cell. Coda's twist: tables are first-class with structured columns and types; rows are addressable individually; columns can hold formulas.
Doc IDs look like dXXXXXXXXXX (10-char prefix d). Visible in the doc URL.
Table IDs look like grid-XXXXX. Discover via coda_list_tables(docId).
…(continued in the in-app connector instructions)
Step 2 — Install the adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Step 3 — Add the connector in Gemini
Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (
https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide showsYOUR_SERVER_ID.
Gemini CLI reads MCP servers from ~/.gemini/settings.json (or %APPDATA%\gemini\settings.json on Windows). Add:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID",
"headers": { "X-API-Key": "YOUR_MCP_API_KEY" }
}
}
}
- Get your MCP API key from AnythingMCP → MCP Servers → your server → API keys.
- Save the file and restart
gemini. - Run
/mcpinside the Gemini CLI —Codashould be listed as available. - Vertex AI Studio: pass
https://cloud.anythingmcp.com/mcp/YOUR_SERVER_IDto thetoolsarray of your request with the sameX-API-Keyheader.
Available tools
| Tool | What it does |
|---|---|
coda_whoami | Return the user the token belongs to |
coda_list_docs | List docs the user can access |
coda_get_doc | Fetch a single doc by ID |
coda_list_tables | List tables in a doc |
coda_list_columns | List columns in a table |
coda_list_rows | List rows in a table or view |
coda_get_row | Fetch a single row by ID |
coda_insert_rows | Insert (or upsert with keyColumns) rows into a table |
coda_update_row | Update a specific row by ID |
coda_delete_row | Delete a single row by ID |
coda_delete_rows | Bulk-delete rows by IDs (more efficient than per-row) |
coda_get_formula_result | Evaluate a named formula on a doc |
coda_get_mutation_status | Check the status of an async mutation (insert/update/delete) by its requestId returned from those calls |
FAQ
Does Gemini 1.5 Pro or 2.x support MCP? Yes — Gemini CLI ≥ 0.4 and Vertex AI tools API both accept MCP httpUrl connectors with custom headers.
Next steps
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