airtable-mcp-server: Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases

by domdomegg · MCP Server · ★ 455

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 76/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

airtablemcp-servermodel-context-protocol

Quick Facts

Stars455
Forks132
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score76/100
Open Issues2
Last Updated2026-10-25
Created2024-12-12
Platformsmcp, node
Est. Tokens~16k

About airtable-mcp-server

airtable-mcp-server A Model Context Protocol server that provides read and write access to Airtable databases. This server enables LLMs to inspect database schemas, then read and write records. https://github.com/user-attachments/assets/c8285e76-d0ed-4018-94c7-20535db6c944 Installation Step 1: Create an Airtable personal access token by clicking here. Details: Name: Anything you want e.g.

Compatible Skills

These tools work well together with airtable-mcp-server for enhanced workflows:

  • mcp-server — semantic(0.60)+same_lang+similar_pop+shared_platform (51%)
  • fetch-mcp — semantic(0.42)+same_lang+similar_pop+shared_platform (50%)
  • mcp-server-commands — semantic(0.54)+same_lang+similar_pop+shared_platform (49%)
  • markdownify-mcp — semantic(0.39)+same_lang+similar_pop+shared_platform (49%)
  • mcp — semantic(0.38)+same_lang+similar_pop+shared_platform (48%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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