> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tight.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Embedding & Integration

> Embed accounting functionality into your platform using the Tight Model Context Protocol (MCP) server

## Overview

Tight Embedding & Integration MCP tools enable AI assistants and agents to interact with the Tight API, embed user
experiences, and search its documentation.

## Available Tools

### Search Tight Documentation

The `search_tight_documentation` tool searches across Tight's full documentation, including API references, integration
guides, and embeddable UI component docs. Use this tool to answer questions, look up parameters, and find working code
examples as you build.

<Tip>
  Connect your editor's AI agent (e.g., Claude Code, Cursor, VS Code Copilot) to Tight's MCP server so it can answer Tight-specific questions inline as you write code. See the [MCP Overview](/ai/mcp-tools/mcp-overview) for setup instructions.
</Tip>