Best for
- Teams looking to integrate Airtable data into AI workflows
- Individual developers who want to use natural language to operate Airtable data
- Scenarios requiring rapid prototyping or automation
A
Airtable MCP Server
Community
Give AI systems read and write access to your Airtable databases
GitHub source repository ↗
44FMRS · D
The server is feature-rich, covering major Airtable operations, suitable for developers and teams integrating AI assistants. However, attention must be paid to token management and security risks, especially in HTTP mode.
This is a Model Context Protocol (MCP) server that provides read and write access to Airtable databases. It enables LLMs to inspect database schemas, then read and write records. It supports a variety of tools including listing records, searching records, creating tables, updating fields, and adding comments. The server requires an Airtable personal access token with scopes such as schema.bases:read and data.records:read. It uses stdio transport by default, and also supports HTTP mode (with security caveats).
Tools
list_records
List records from a specified Airtable table
search_records
Search for records containing specific text
list_bases
List all accessible Airtable bases
list_tables
List all tables in a specific base
describe_table
Get detailed information about a specific table
get_record
Get a specific record by ID
create_record
Create a new record in a table
update_records
Update one or more records in a table
delete_records
Delete one or more records from a table
create_table
Create a new table in a base
update_table
Update a table's name or description
create_field
Create a new field in a table
update_field
Update a field's name or description
create_comment
Create a comment on a record
list_comments
List comments on a record
Setup
- Generate an Airtable personal access token (https://airtable.com/create/tokens/new) with scopes: schema.bases:read and data.records:read (optionally write scopes). 2. Use the install-mcp tool (https://adamjones.me/install-mcp/?config=...) to generate MCP client configuration, or manually configure. 3. Set the environment variable AIRTABLE_API_KEY to your token. 4. For stdio mode, run npx -y airtable-mcp-server.
Fit and risk
Not for
- Teams requiring complex permission control or auditing (the server uses a single token)
- Scenarios requiring real-time collaboration or complex data relationships
- Users with high security requirements who cannot restrict network exposure
Required permissions
- Requires an Airtable personal access token
- Token needs at least schema.bases:read and data.records:read scopes
- Optional write scopes: schema.bases:write, data.records:write, data.recordComments:read, data.recordComments:write
- Token must have access to target bases
Risks and side effects
- Token leakage could allow malicious reads/writes of data
- HTTP mode has no built-in authentication and may be vulnerable to DNS rebinding attacks
- Delete or update operations are irreversible; mistakes may cause data loss
- Shared tokens may exceed intended access scope
Troubleshooting
- Confirm that the AIRTABLE_API_KEY environment variable is set correctly
- Check that the token's scopes include the required operations
- Ensure the token has access to the target base
- If using HTTP mode, ensure the network environment is secure
- Check server logs for error details
Use cases
Allow AI assistants to query and update business data in Airtable
Automate data organization and bulk record updates
Use Airtable as a knowledge base for AI to read
Create and manage table schemas through AI
Supported clients
Claude DesktopFull support
Claude CodeFull support
CursorFull support
ClineFull support
VS CodeFull support