Airtable OAuth MCP Server
Enables interaction with Airtable bases through OAuth 2.0 authentication, providing complete API coverage for all Airtable operations including listing bases, managing tables, and performing record operations (creating, reading, updating, deleting, searching, and filtering records).
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Airtable OAuth MCP Server list tables in my project management base"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Airtable OAuth MCP Server
A production-ready Model Context Protocol (MCP) server for Airtable with secure OAuth 2.0 authentication. This server enables AI assistants and applications to interact with Airtable bases through a standardized MCP interface, providing complete API coverage for all Airtable operations.
๐ Features
Core Functionality
๐ OAuth 2.0 Authentication - Secure token-based authentication with Airtable
๐ Complete Airtable API Coverage - 10 comprehensive MCP tools covering all operations
โก FastMCP Framework - Built on the high-performance FastMCP framework
โ๏ธ Cloud-Ready - Production-ready deployment support
๐ Dual Transport - Support for both STDIO and HTTP transport protocols
Security & Reliability
๐ Environment-based Configuration - Secure credential management
โ Type Safety - Full type hints and validation with Pydantic
๐งช Comprehensive Testing - Unit tests with pytest and coverage reporting
๐ Code Quality - Linting with Ruff and type checking with MyPy
Developer Experience
๐ Rich Documentation - Comprehensive setup and usage guides
๐ง Easy Setup - Simple installation with uv package manager
๐ฏ Typed Parameters - Clear, typed tool parameters for better IDE support
๐ Flexible Querying - Advanced filtering, sorting, and search capabilities
Related MCP server: Airtable MCP Server
๐ Prerequisites
Python 3.11+ - Latest Python version for optimal performance
uv - Fast Python package manager (install guide)
Airtable Developer Account - To create OAuth applications (sign up)
๐ Quick Start
1. Installation
Clone the repository and install dependencies:
git clone https://github.com/onimsha/airtable-mcp-server-oauth.git
cd airtable-mcp-server-oauth
uv sync2. Airtable OAuth Setup
Create an Airtable OAuth Application:
Visit Airtable Developer Hub
Create a new OAuth integration
Note your
Client IDandClient SecretSet redirect URI to
http://localhost:8000/oauth/callback
3. Environment Configuration
Copy the environment template and configure your credentials:
cp .env.example .envEdit .env with your values:
# Airtable OAuth Configuration
AIRTABLE_CLIENT_ID="your_airtable_client_id_here"
AIRTABLE_CLIENT_SECRET="your_airtable_client_secret_here"
AIRTABLE_REDIRECT_URI="http://localhost:8000/oauth/callback"
# Server Configuration
HOST="0.0.0.0"
PORT=8000
LOG_LEVEL="INFO"4. Testing with MCP Inspector
Use the official MCP Inspector to test and interact with your server:
Start the server:
uv run python -m airtable_mcp httpOpen MCP Inspector: Visit https://modelcontextprotocol.io/docs/tools/inspector
Connect to your server:
Select "HTTP Streaming" transport
Enter the URL:
http://localhost:8000/mcpClick "Connect"
Authenticate with Airtable:
The server will guide you through OAuth authentication
Use the inspector to test available MCP tools
5. Run the Server
STDIO Transport (default):
uv run python -m airtable_mcp
# or
uv run airtable-oauth-mcpHTTP Transport:
uv run python -m airtable_mcp http
# or with custom host/port
uv run python -m airtable_mcp http localhost 8001Additional Options:
# Set log level
uv run python -m airtable_mcp --log-level DEBUG
# Show help
uv run python -m airtable_mcp --help
# Show version
uv run python -m airtable_mcp --versionThe HTTP server will be available at http://localhost:8000/ (or custom host:port) with OAuth endpoints for web integration.
MCP Tools Available
The server provides 10 MCP tools for Airtable operations:
Base Operations:
list_bases()- List all accessible baseslist_tables(base_id, detail_level?)- List tables in a basedescribe_table(base_id, table_id)- Get detailed table schema
Record Operations:
list_records(base_id, table_id, view?, filter_by_formula?, sort?, fields?)- List records with filteringget_record(base_id, table_id, record_id)- Get a specific recordcreate_record(base_id, table_id, fields, typecast?)- Create a single recordcreate_records(base_id, table_id, records, typecast?)- Create multiple recordsupdate_records(base_id, table_id, records, typecast?)- Update multiple recordsdelete_records(base_id, table_id, record_ids)- Delete multiple recordssearch_records(base_id, table_id, filter_by_formula, view?, fields?)- Search records with formulas
All tools now use typed parameters instead of generic args, making them more transparent to MCP clients.
Parameter Flexibility:
fieldsparameter accepts either a single field name (string) or array of field namessortparameter expects array of objects:[{"field": "Name", "direction": "asc"}]
๐ก Usage Examples
Basic Record Operations
# List all records in a table
records = await client.call_tool("list_records", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY"
})
# Create a new record
new_record = await client.call_tool("create_record", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY",
"fields": {
"Name": "John Doe",
"Email": "john@example.com",
"Status": "Active"
}
})
# Search records with filtering
filtered_records = await client.call_tool("search_records", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY",
"filter_by_formula": "AND({Status} = 'Active', {Email} != '')",
"fields": ["Name", "Email", "Status"]
})Advanced Querying
# List records with sorting and filtering
records = await client.call_tool("list_records", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY",
"view": "Grid view",
"filter_by_formula": "{Priority} = 'High'",
"sort": [
{"field": "Created", "direction": "desc"},
{"field": "Name", "direction": "asc"}
],
"fields": ["Name", "Priority", "Created", "Status"]
})
# Batch operations
batch_create = await client.call_tool("create_records", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY",
"records": [
{"fields": {"Name": "Record 1", "Value": 100}},
{"fields": {"Name": "Record 2", "Value": 200}},
{"fields": {"Name": "Record 3", "Value": 300}}
],
"typecast": True
})Schema Discovery
# List all bases you have access to
bases = await client.call_tool("list_bases")
# Get detailed information about a specific table
table_info = await client.call_tool("describe_table", {
"base_id": "appXXXXXXXXXXXXXX",
"table_id": "tblYYYYYYYYYYYYYY"
})
# List all tables in a base
tables = await client.call_tool("list_tables", {
"base_id": "appXXXXXXXXXXXXXX",
"detail_level": "full"
})๐ ๏ธ Development
Getting Started
Fork and Clone:
git clone https://github.com/onimsha/airtable-mcp-server-oauth.git cd airtable-mcp-server-oauthSetup Development Environment:
uv sync --all-extrasRun Tests:
uv run pytest uv run pytest --cov=src/airtable_mcp --cov-report=html
Code Quality
Type Checking:
uv run mypy src/Linting:
uv run ruff check src/
uv run ruff format src/Pre-commit Hooks:
pip install pre-commit
pre-commit installTesting
The project includes comprehensive test coverage:
Unit Tests: Test individual components and functions
Integration Tests: Test OAuth flow and Airtable API interactions
Coverage Reports: Ensure >90% code coverage
# Run all tests
uv run pytest
# Run with coverage
uv run pytest --cov=src/airtable_mcp
# Run specific test files
uv run pytest tests/test_oauth.py
uv run pytest tests/test_tools.pyProject Structure
src/
โโโ airtable_mcp/ # Main MCP server package
โ โโโ __init__.py # Package initialization
โ โโโ __main__.py # Module entry point
โ โโโ main.py # CLI and application entry
โ โโโ api/ # Airtable API client
โ โ โโโ __init__.py
โ โ โโโ client.py # HTTP client for Airtable API
โ โ โโโ exceptions.py # API-specific exceptions
โ โ โโโ models.py # Pydantic models for API responses
โ โโโ mcp/ # MCP server implementation
โ โโโ __init__.py
โ โโโ schemas.py # MCP tool schemas
โ โโโ server.py # FastMCP server with tools
โโโ mcp_oauth_lib/ # Reusable OAuth library
โโโ __init__.py # Library initialization
โโโ auth/ # Authentication components
โ โโโ __init__.py
โ โโโ context.py # Auth context management
โ โโโ middleware.py # OAuth middleware
โ โโโ utils.py # Auth utilities
โโโ core/ # Core OAuth functionality
โ โโโ __init__.py
โ โโโ config.py # OAuth configuration
โ โโโ flow.py # OAuth flow implementation
โ โโโ server.py # OAuth server endpoints
โโโ providers/ # OAuth provider implementations
โ โโโ __init__.py
โ โโโ airtable.py # Airtable OAuth provider
โ โโโ base.py # Base provider interface
โโโ utils/ # OAuth utilities
โโโ __init__.py
โโโ pkce.py # PKCE implementation
โโโ state.py # State managementโ๏ธ Configuration
All configuration is handled through environment variables (loaded from .env):
Required Variables
AIRTABLE_CLIENT_ID- OAuth client ID from AirtableAIRTABLE_CLIENT_SECRET- OAuth client secretAIRTABLE_REDIRECT_URI- OAuth callback URL
Optional Variables
HOST- Server host (default:0.0.0.0)PORT- Server port (default:8000)LOG_LEVEL- Logging level (default:INFO)MCP_SERVER_NAME- Server name (optional)MCP_SERVER_VERSION- Server version (optional)
๐ค Contributing
We welcome contributions! Please see our contribution guidelines:
Fork the repository and create a feature branch
Write tests for any new functionality
Ensure code quality with our linting and formatting tools
Update documentation for any API changes
Submit a pull request with a clear description
Contribution Areas
๐ Bug fixes - Help us squash bugs
โจ New features - Add new Airtable API endpoints
๐ Documentation - Improve setup guides and examples
๐งช Testing - Increase test coverage
๐ Performance - Optimize API calls and caching
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
FastMCP - Excellent MCP framework
Airtable - Powerful database platform
Model Context Protocol - Standard for AI tool integration
๐ Documentation
Additional Resources
๐ Support
Issues: GitHub Issues
Discussions: GitHub Discussions
Documentation: Project Wiki
Available Tools
10 toolscreate_recordC
Create a single record
Inputs: base_id (required), table_id (required), fields (required), typecast. Returns: object
create_recordsC
Create multiple records
Inputs: base_id (required), table_id (required), records (required), typecast. Returns: result
delete_recordsC
Delete multiple records
Inputs: base_id (required), table_id (required), record_ids (required). Returns: result
describe_tableB
Get detailed information about a specific table
Inputs: base_id (required), table_id (required). Returns: object
get_recordB
Get a specific record by ID
Inputs: base_id (required), table_id (required), record_id (required). Returns: object
list_basesA
List all accessible Airtable bases
Inputs: no named parameters. Returns: result
list_recordsB
List records from a table with optional filtering
Inputs: base_id (required), table_id (required), view, filter_by_formula, +2 more. Returns: result
list_tablesA
List tables in a specific base
Inputs: base_id (required), detail_level. Returns: result
search_recordsB
Search records using a formula filter
Inputs: base_id (required), table_id (required), filter_by_formula (required), view, +1 more. Returns: result
update_recordsC
Update multiple records
Inputs: base_id (required), table_id (required), records (required), typecast. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogโฆ
TDQS
Scored across 10 tools
Each tool has a clearly distinct purpose with no ambiguity: create_record vs create_records handles single vs batch creation, list_records vs search_records provides listing vs filtered searching, and get_record vs update_records vs delete_records covers different CRUD operations. The descriptions reinforce these distinctions, making tool selection straightforward.
All tools follow a consistent verb_noun naming pattern using snake_case (e.g., create_record, list_bases, update_records). The verbs are appropriate and predictable (create, delete, describe, get, list, search, update), creating a coherent and readable toolset.
With 10 tools, this server is well-scoped for Airtable operations. Each tool earns its place by covering essential CRUD operations, base/table management, and search capabilities. The count is neither too sparse nor bloated, fitting typical agent workflows effectively.
The toolset provides complete coverage for Airtable interactions: CRUD operations on records (create, get, update, delete, list, search), base and table management (list_bases, list_tables, describe_table), and support for both single and batch operations. There are no obvious gaps that would hinder agent workflows.
Maintenance
Related MCP Connectors
Hosted Airtable MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
Official Airtable MCP server โ database and operations layer for agents.
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Official Fibery MCP server: query and update your workspace from any AI client via OAuth.
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