databasesdeveloper-tools

AITable MCP Server

hamchowderr

by hamchowderr

AITable MCP Server: full AITable API access and workspace API, datasheet API, and record management API—file uploads and

Enables interaction with AITable workspaces through comprehensive API access, supporting record and field management, datasheet creation, file uploads, and workspace search across 16 tools with both local and remote deployment options.

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16 different tools availableBoth local and remote deploymentComplete workspace management

best for

  • / Teams using AITable for project management
  • / Developers building AITable integrations
  • / Data analysts working with AITable datasets
  • / Organizations automating AITable workflows

capabilities

  • / Manage records and fields in AITable datasheets
  • / Create and configure new datasheets
  • / Upload and manage files in workspaces
  • / Search across workspace content
  • / Query datasheet metadata and structure
  • / Handle workspace permissions and settings

what it does

Connects to AITable workspaces for managing records, fields, and datasheets through comprehensive API access. Supports file uploads and workspace search across multiple tools.

about

AITable MCP Server is a community-built MCP server published by hamchowderr that provides AI assistants with tools and capabilities via the Model Context Protocol. AITable MCP Server: full AITable API access and workspace API, datasheet API, and record management API—file uploads and It is categorized under databases, developer tools.

how to install

You can install AITable MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

AITable MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

AITable MCP Server

AITable

Model Context Protocol (MCP) server for integrating with AITable platform.

⚠️ Important: AITable has been discontinued. If you're looking to migrate to Bika (the successor platform), check out the Bika MCP Server.

AITable LTD Holders: Claim your free Bika account by filling out this migration form (available only for AITable LTD users).

Overview

This MCP server provides integration with AITable's API, enabling AI assistants to:

  • Query and filter datasheet records
  • Create, update, and delete records
  • Upload and manage attachments
  • Work with fields, views, and nodes
  • Create embeddable links

Features

  • Records Management: Full CRUD operations on AITable records
  • Fields Management: Create, query, and delete fields
  • Views & Nodes: Access datasheet views and workspace nodes
  • Attachments: Upload and manage files
  • Embed Links: Create and manage embeddable links
  • Formula Resources: Access AITable formula documentation

Prerequisites

  • Node.js >= 18.0.0
  • npm or pnpm
  • AITable account with API access token

Installation

Option 1: Install via npm (Recommended)

Once published, you can install directly via npx:

# No installation needed! Run directly with npx
npx aitable-mcp

Option 2: Install from Source

# Clone the repository
git clone https://github.com/hamchowderr/aitable-mcp.git
cd aitable-mcp

# Install dependencies
npm install

# Build the project
npm run build

Configuration

Environment Variables

The server requires the following environment variables:

VariableRequiredDescription
AITABLE_API_TOKENYesYour AITable API access token
SPACE_IDYesYour AITable space ID

Setting Environment Variables

Option 1: Environment variables

# Windows
set AITABLE_API_TOKEN=your-api-token-here
set SPACE_ID=your-space-id

# macOS/Linux
export AITABLE_API_TOKEN="your-api-token-here"
export SPACE_ID="your-space-id"

Option 2: Create a .env file

Create a .env file in the project root:

AITABLE_API_TOKEN=your-api-token-here
SPACE_ID=your-space-id

Usage

Option 1: Claude Desktop (Stdio Transport)

The recommended way to use this MCP server is with Claude Desktop using stdio transport.

Configuration File Locations

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Using npx (Recommended)

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "aitable": {
      "command": "npx",
      "args": ["-y", "aitable-mcp"],
      "env": {
        "AITABLE_API_TOKEN": "your-token-here",
        "SPACE_ID": "your-space-id"
      }
    }
  }
}

Using Local Installation

For development or local installations:

{
  "mcpServers": {
    "aitable": {
      "command": "node",
      "args": ["C:\absolute\path\	o\aitable-mcp\dist\stdio-server.js"],
      "env": {
        "AITABLE_API_TOKEN": "your-token-here",
        "SPACE_ID": "your-space-id"
      }
    }
  }
}

Important: Restart Claude Desktop after updating the configuration.

Option 2: Testing with MCP Inspector

Test your server locally with the official MCP Inspector:

# Run the inspector
npm run inspector

# Or run directly
npx @modelcontextprotocol/inspector dist/stdio-server.js

This will:

  1. Start the MCP server
  2. Launch the inspector web interface at http://localhost:6274
  3. Allow you to test tools, resources, and prompts interactively

Option 3: Running Standalone (Stdio)

Run the server directly for stdio transport:

# Build and start
npm run build
npm start

# Development mode with watch
npm run dev

Option 4: Custom Connector (HTTP Transport via Vercel)

Deploy as a custom connector for HTTP-based MCP access.

Deploy to Vercel

  1. Initial Deployment:

    # Install Vercel CLI if needed
    npm install -g vercel
    
    # Deploy to Vercel
    npx vercel@latest
    
  2. Production Deployment:

    npx vercel@latest --prod
    
  3. Set Environment Variables:

    In your Vercel project settings (Settings → Environment Variables), add:

    • AITABLE_API_TOKEN - Your AITable API token (required for authenticating with AITable)
    • SPACE_ID - Your AITable space ID (required)

    Important: Ensure both variables are enabled for all environments (Production, Preview, and Development). If Preview is unchecked, preview deployment URLs will fail with "Connection refused".

  4. Disable Deployment Protection (Required for MCP):

    In your Vercel project settings (Settings → Deployment Protection):

    • Turn OFF "Vercel Authentication"
    • This is required for Claude Desktop and other MCP clients to connect
    • Your data remains secure through the API token configured in step 3
  5. Configure as Custom Connector in Claude Desktop:

    IMPORTANT: Custom connectors must be configured via the Claude Desktop UI, NOT via claude_desktop_config.json.

    To add the custom connector:

    1. Open Claude Desktop
    2. Go to Settings → Connectors
    3. Click Add Custom Connector
    4. Enter your deployment URL: https://your-project.vercel.app/mcp
    5. Save and restart Claude Desktop

    Note: Make sure to include /mcp at the end of the URL!

  6. Test the Deployment:

    # Test with the test script
    node scripts/test-streamable-http-client.mjs https://your-project.vercel.app
    

Deployment Options

Stdio vs HTTP Transport:

  • Stdio (Recommended): Lower latency, direct process communication, best for Claude Desktop
  • HTTP (Custom Connector): Centralized deployment, multiple clients, better for cloud deployments

Which to use?

  • Use stdio for local Claude Desktop integration
  • Use HTTP for centralized deployments, multiple users, or cloud-based AI clients

Security

Authentication Overview

This MCP server uses different authentication strategies depending on the transport:

Stdio Transport (Recommended for Personal Use)

  • Uses environment variables for AITable API authentication
  • No client authentication required (local process, no network exposure)
  • Most secure for personal use
  • Configure via claude_desktop_config.json

HTTP Transport (Custom Connector)

  • Deployed to Vercel as a serverless function
  • Requires disabling Vercel Deployment Protection
  • CORS-enabled for browser-based access
  • Environment variables stored securely in Vercel

Security Best Practices

IMPORTANT:

  • ⚠️ Keep your AITABLE_API_TOKEN secret - it grants full access to your AITable data
  • ⚠️ Keep your deployment URL private - share only with trusted users
  • ⚠️ Disable Vercel Deployment Protection for MCP clients to connect
  • ✅ Use environment variables in Vercel (never commit tokens to git)
  • ✅ Rotate your API token periodically
  • ✅ Monitor access logs in Vercel dashboard
  • ✅ For personal use, prefer stdio transport over HTTP

Architecture

This MCP server supports dual transport following official MCP patterns:

Stdio Transport (src/stdio-server.ts)

  • Primary entry point for Claude Desktop
  • Direct process communication via stdin/stdout
  • Low latency, perfect for local development
  • Executable via npx or node dist/stdio-server.js

HTTP Transport (api/server.ts)

  • Vercel serverless function with CORS support
  • Uses mcp-handler library for HTTP transport
  • Supports custom connector deployments
  • All requests handled at root path with catch-all routing

Both transports share the same core business logic while providing different communication mechanisms.

Project Structure

aitable-mcp/
├── src/
│   ├── stdio-server.ts    # Stdio entry point
│   ├── http-server.ts     # Local HTTP server for testing
│   ├── aitable-tools.ts   # MCP tool implementations
│   ├── formula-resource.ts # Formula documentation provider
│   ├── types.ts           # TypeScript type definitions
│   └── *.md               # Formula documentation files
├── api/
│   └── server.ts          # HTTP entry point (Vercel)
├── public/
│   └── index.html         # Landing page
├── scripts/
│   ├── test-client.mjs                    # SSE transport tester
│   └── test-streamable-http-client.mjs    # HTTP transport tester
├── dist/                  # Compiled output
├── package.json
├── tsconfig.json
├── vercel.json            # Vercel configuration
└── README.md

Available Tools (16)

The MCP server provides comprehensive AITable integration tools:

Records Management

  • get_records - Query records with filtering, sorting, and pagination
  • create_records - Create new records (max 10 per request)
  • update_records - Update existing records (max 10 per request)
  • delete_records - Delete records (max 10 per request)

Fields Management

  • get_fields - Get field metadata from datasheets
  • create_field - Create new fields in datasheets
  • delete_field - Delete fields from datasheets

Views & Datasheets

  • get_views - Get views from datasheets
  • create_datasheet - Create new datasheets with custom fields

Attachments

  • upload_attachment - Upload files to datasheets

Nodes & Workspace

  • get_node_list - Get list of files in workspace
  • search_nodes - Search nodes by type, permissions, and keywords
  • get_node_detail - Get detailed information about specific nodes

Embed Links

  • create_embed_link - Create embeddable links for nodes
  • get_embed_links - List all embed links for a node
  • delete_embed_link - Delete/disable embed links

Available Resources (8)

Formula reference documentation:

  • formula_overview - Quick reference guide to AITable formulas
  • `

FAQ

What is the AITable MCP Server MCP server?
AITable MCP Server is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for AITable MCP Server?
This profile displays 34 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Direct Database Queries from AI

Enable Claude to query your database directly using natural language

Example

Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly

Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster

Data Analysis & Reporting

Generate complex reports and analytics without leaving conversation

Example

Analyze sales trends, cohort retention, user behavior patterns conversationally

Democratize data access—non-technical team members can query databases

Schema Exploration

Understand database structure, relationships, and data models

Example

'Explain the user_orders table schema and its relationships'

Onboard engineers faster, explore unfamiliar databases efficiently

Data Validation & Quality Checks

Run data quality queries to catch anomalies and inconsistencies

Example

Find duplicate records, missing values, orphaned foreign keys automatically

Maintain data integrity with less manual SQL work

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor with MCP support
  • Database credentials (read-only recommended for safety)
  • Network access from Claude client to database
  • Understanding of database security and access control

Time Estimate

15-30 minutes including configuration and testing

Installation Steps

  1. 1.Install MCP server: npm install -g @modelcontextprotocol/server-[name]
  2. 2.Configure database connection in Claude Desktop config (~/.claude/mcp.json)
  3. 3.Provide connection string: host, port, database, username, password
  4. 4.Restart Claude Desktop to load MCP server
  5. 5.Test connection: 'List all tables in database'
  6. 6.Run simple query: 'Show me 5 rows from users table'
  7. 7.Verify results and permissions are correct
  8. 8.Document query patterns for team use

Troubleshooting

  • Connection refused: Check database is running and network accessible
  • Authentication failed: Verify credentials, check user permissions
  • Claude can't see tables: Grant appropriate read permissions to database user
  • Slow queries: Add indexes, limit result set size, use read replicas
  • MCP server not loading: Check config syntax, restart Claude Desktop

Best Practices

✓ Do

  • +Use read-only database credentials to prevent accidental writes
  • +Connect to read replica, not production primary database
  • +Set query timeout limits to prevent long-running queries
  • +Document database schema and common queries for AI context
  • +Monitor query performance and optimize slow queries
  • +Use connection pooling for better performance
  • +Test with non-production data first

✗ Don't

  • Don't use production write credentials—risk of data corruption
  • Don't query production database during peak traffic hours
  • Don't expose sensitive PII without proper access controls
  • Don't skip query result validation—AI can misinterpret schema
  • Don't allow unlimited result set sizes—set LIMIT clauses
  • Don't share database credentials in plain text config files

💡 Pro Tips

  • Create database views for common queries to simplify AI access
  • Add schema comments/descriptions so AI understands column meanings
  • Use semantic table/column names ('customer_lifetime_value' not 'clv')
  • Set up query logging to audit what Claude is querying
  • Create saved query templates for recurring analysis
  • Combine with data visualization tools for better insights

Technical Details

Architecture

MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.

Protocols

  • Model Context Protocol (MCP)
  • Database-specific protocols (PostgreSQL, MySQL, MongoDB)

Compatibility

  • PostgreSQL
  • MySQL
  • SQLite
  • MongoDB
  • Redis

When to Use This

✓ Use When

Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.

✗ Avoid When

Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.

Integration

  • Read replica connection for analytics queries
  • Database view layer to abstract complex joins
  • Query result caching for repeated questions
  • Audit logging of all AI-generated queries

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.734 reviews
  • Chaitanya Patil· Dec 28, 2024

    According to our notes, AITable MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Piyush G· Nov 19, 2024

    We wired AITable MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Noah Kapoor· Nov 11, 2024

    AITable MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Noor Perez· Nov 3, 2024

    Useful MCP listing: AITable MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Hassan Lopez· Oct 22, 2024

    AITable MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Shikha Mishra· Oct 10, 2024

    AITable MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Kaira Reddy· Oct 2, 2024

    Useful MCP listing: AITable MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Omar Gonzalez· Sep 17, 2024

    I recommend AITable MCP Server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Noor Rahman· Sep 13, 2024

    According to our notes, AITable MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Noor Choi· Sep 5, 2024

    AITable MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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