Sanity MCP Server

Created By
andyciggya year ago
Overview

What is Sanity MCP Server?

Sanity MCP Server is a tool designed to enhance content operations by integrating AI capabilities into the Sanity platform. It allows users to manage and explore their content through natural language interactions with AI tools.

How to use Sanity MCP Server?

To use the Sanity MCP Server, deploy your Sanity Studio with a schema manifest, obtain your API credentials, and configure the MCP server settings in your application. You can then interact with the server using various AI tools that support the Model Context Protocol.

Key features of Sanity MCP Server?

  • 🤖 Content Intelligence: AI can explore and understand your content library.
  • 🔄 Content Operations: Automate tasks using natural language instructions.
  • 📊 Schema-Aware: AI respects your content structure and validation rules.
  • 🚀 Release Management: Easily plan and organize content releases.
  • 🔍 Semantic Search: Find content based on meaning rather than just keywords.

Use cases of Sanity MCP Server?

  1. Automating content creation and updates through AI.
  2. Managing content releases efficiently.
  3. Enhancing search capabilities with semantic understanding.

FAQ from Sanity MCP Server?

  • Can I use Sanity MCP Server with any application?

Yes, it can be used with any application that supports the Model Context Protocol.

  • What are the prerequisites for using the MCP server?

You need to deploy your Sanity Studio with a schema manifest and obtain API credentials.

  • Is there a risk when using AI with production datasets?

Yes, using a token with write access can lead to destructive actions, so it's recommended to use a development or staging dataset for testing.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
andyciggy
Star
0
Language
TypeScript
License
MIT license

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

10 hours ago