Airtable OAuth MCP Server
A production-ready Model Context Protocol server that enables AI assistants and applications to interact with Airtable bases through a standardized interface with secure OAuth 2.0 authentication.
README
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.
🚀 Features
Core Functionality
- 🔐 OAuth 2.0 Authentication - Secure token-based authentication with Airtable
- 📊 Complete Airtable API Coverage - 10 comprehensive MCP tools covering all operations
- ⚡ FastMCP Framework - Built on the high-performance FastMCP framework
- ☁️ Cloud-Ready - Production-ready deployment support
- 🔄 Dual Transport - Support for both STDIO and HTTP transport protocols
Security & Reliability
- 🔑 Environment-based Configuration - Secure credential management
- ✅ Type Safety - Full type hints and validation with Pydantic
- 🧪 Comprehensive Testing - Unit tests with pytest and coverage reporting
- 📝 Code Quality - Linting with Ruff and type checking with MyPy
Developer Experience
- 📚 Rich Documentation - Comprehensive setup and usage guides
- 🔧 Easy Setup - Simple installation with uv package manager
- 🎯 Typed Parameters - Clear, typed tool parameters for better IDE support
- 🔍 Flexible Querying - Advanced filtering, sorting, and search capabilities
📋 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)
🚀 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 sync
2. Airtable OAuth Setup
- Create an Airtable OAuth Application:
- Visit Airtable Developer Hub
- Create a new OAuth integration
- Note your
Client IDandClient Secret - Set redirect URI to
http://localhost:8000/oauth/callback
3. Environment Configuration
Copy the environment template and configure your credentials:
cp .env.example .env
Edit .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 http -
Open MCP Inspector: Visit https://modelcontextprotocol.io/docs/tools/inspector
-
Connect to your server:
- Select "HTTP Streaming" transport
- Enter the URL:
http://localhost:8000/mcp - Click "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-mcp
HTTP Transport:
uv run python -m airtable_mcp http
# or with custom host/port
uv run python -m airtable_mcp http localhost 8001
Additional 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 --version
The 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"}]
💡 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"
})
🛠️ Development
Getting Started
-
Fork and Clone:
git clone https://github.com/onimsha/airtable-mcp-server-oauth.git cd airtable-mcp-server-oauth -
Setup Development Environment:
uv sync --all-extras -
Run 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 install
Testing
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.py
Project Structure
src/
├── airtable_mcp/ # Main MCP server package
│ ├── __init__.py # Package initialization
│ ├── __main__.py # Module entry point
│ ├── main.py # CLI and application entry
│ ├── api/ # Airtable API client
│ │ ├── __init__.py
│ │ ├── client.py # HTTP client for Airtable API
│ │ ├── exceptions.py # API-specific exceptions
│ │ └── models.py # Pydantic models for API responses
│ └── mcp/ # MCP server implementation
│ ├── __init__.py
│ ├── schemas.py # MCP tool schemas
│ └── server.py # FastMCP server with tools
└── mcp_oauth_lib/ # Reusable OAuth library
├── __init__.py # Library initialization
├── auth/ # Authentication components
│ ├── __init__.py
│ ├── context.py # Auth context management
│ ├── middleware.py # OAuth middleware
│ └── utils.py # Auth utilities
├── core/ # Core OAuth functionality
│ ├── __init__.py
│ ├── config.py # OAuth configuration
│ ├── flow.py # OAuth flow implementation
│ └── server.py # OAuth server endpoints
├── providers/ # OAuth provider implementations
│ ├── __init__.py
│ ├── airtable.py # Airtable OAuth provider
│ └── base.py # Base provider interface
└── utils/ # OAuth utilities
├── __init__.py
├── pkce.py # PKCE implementation
└── state.py # State management
⚙️ 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)
🤝 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
- 🐛 Bug fixes - Help us squash bugs
- ✨ New features - Add new Airtable API endpoints
- 📚 Documentation - Improve setup guides and examples
- 🧪 Testing - Increase test coverage
- 🚀 Performance - Optimize API calls and caching
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
- FastMCP - Excellent MCP framework
- Airtable - Powerful database platform
- Model Context Protocol - Standard for AI tool integration
📚 Documentation
Additional Resources
📞 Support
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: Project Wiki
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