rashidazarang/airtable-mcp

Overview

Connects your AI assistant to Airtable so it can query, create, and update records in your bases using plain-English requests instead of clicking through the Airtable interface. It handles both reading and writing, so it can answer questions about your data and make the update in the same conversation. A practical option for teams that run their tracking or lightweight CRM through Airtable.

Best for

Best for
Teams running lightweight CRM or tracking in Airtable who want conversational updates

Use cases

• Query Airtable records to answer a question about current data
• Update or create a record from a plain-English request
• Automate a recurring data entry workflow in Airtable
• Build a simple assistant that reads from Airtable as a backend

How to use

Install

codex mcp add airtable -- npx -y @rashidazarang/airtable-mcp

Tools exposed

• list_bases
• search_records
• list_records
• get_record
• delete_record
• batch_upsert_records
• list_tables
• get_base_schema
• list_field_types
• get_table_views
• create_table
• update_table
• delete_table
• create_field
• update_field
• delete_field
• batch_create_records
• batch_update_records
• batch_delete_records
• list_webhooks

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, Cline, VS Code, ChatGPT

Example client config

{\n  "mcpServers": {\n    "airtable": {\n      "command": "npx",\n      "args": ["-y", "@rashidazarang/airtable-mcp"],\n      "env": {\n        "AIRTABLE_TOKEN": "YOUR_AIRTABLE_TOKEN",\n        "AIRTABLE_BASE_ID": "YOUR_BASE_ID"\n      }\n    }\n  }\n}

Notes

A TypeScript-based MCP server that exposes Airtable bases, tables, and records to AI assistants through Anthropic’s Model Context Protocol. It translates natural language requests into structured Airtable API calls, enabling read and write operations without manual API coding.

84 stars on GitHub. Last updated 2026-02-20. Licensed MIT.

Use cases

• Query and update Airtable records via natural language in Claude or other MCP-compatible assistants
• Automate data entry and retrieval workflows between AI agents and Airtable bases
• Build custom AI tools that interact with Airtable as a backend data store

Pros

• Simplifies Airtable integration for AI applications by abstracting API complexity
• Open source with TypeScript for easy customization and extension
• Supports both reading and writing data through a standardized protocol

Cons

• Requires an MCP-compatible client (e.g., Claude) to function
• Limited to Airtable’s API rate limits and field type constraints
• Small community (84 stars) may mean fewer examples or support

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.