# com.airtable/mcp

> Use this tool when you need to integrate a database and operations layer for AI agents, providing a centralized management system for data-driven decision making. It solves problems related to data storage, retrieval, and manipulation, enabling seamless interactions between agents and their environment. With inputs such as agent requests and outputs like query results, use this tool in contexts where agent autonomy and data-driven actions are crucial.

Canonical page: https://skillsregistry.net/skills/com-airtable-mcp  
JSON: https://api.skillsregistry.net/v1/skills/com-airtable-mcp

## Description

Official Airtable MCP server — database and operations layer for agents.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.airtable%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.airtable.com/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "com-airtable-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-airtable-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-airtable-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt