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AI Features and Integrations Reference
Complete guide for Mintlify's AI-powered features including AI assistant, llms.txt, MCP, and automation.
AI Assistant
Built-in AI assistant for documentation search and Q&A.
Configuration
Enable AI assistant in docs.json:
{
"search": {
"prompt": "Ask me anything about our documentation..."
}
}
Features
Conversational Search:
- Natural language queries
- Context-aware responses
- Source citations from docs
- Follow-up questions
Capabilities:
- Search across all documentation
- Answer technical questions
- Provide code examples
- Navigate to relevant pages
- Suggest related content
Customization
Custom Prompt:
{
"search": {
"prompt": "How can I help you with the API?",
"placeholder": "Ask about authentication, endpoints, or SDKs..."
}
}
Search Scope:
{
"search": {
"scope": ["api", "guides"],
"exclude": ["internal", "deprecated"]
}
}
llms.txt
Optimize documentation for LLM consumption and indexing.
What is llms.txt?
Special file format that makes documentation machine-readable for AI models:
- Structured content for LLMs
- Optimized token usage
- Hierarchical organization
- Metadata for context
Auto-Generation
Mintlify automatically generates llms.txt from your documentation.
Access: https://docs.example.com/llms.txt
Manual Configuration
Customize llms.txt generation:
{
"ai": {
"llmsTxt": {
"enabled": true,
"include": ["introduction", "api/*", "guides/*"],
"exclude": ["internal/*", "deprecated/*"],
"format": "structured"
}
}
}
llms.txt Format
Generated file structure:
# Product Name Documentation
## Overview
Brief description of product and documentation
## Getting Started
> /introduction
Quick introduction to get started
> /quickstart
Step-by-step quickstart guide
## API Reference
> /api/authentication
Authentication methods and API keys
> /api/users
User management endpoints
> /api/posts
Post creation and management
## Guides
> /guides/deployment
Deployment guide for production
> /guides/security
Security best practices
Use Cases
Feed to LLMs:
- Provide entire docs context to ChatGPT, Claude, etc.
- Enable AI to answer questions about your product
- Generate code examples based on documentation
RAG Systems:
- Index for retrieval-augmented generation
- Build custom AI assistants
- Create documentation chatbots
skill.md
Make documentation agent-ready with skill definitions.
What is skill.md?
Defines your API/product as a "skill" that AI agents can execute:
- Function signatures
- Parameter schemas
- Authentication requirements
- Example usage
Generation
Mintlify auto-generates skill.md from OpenAPI specs.
Access: https://docs.example.com/skill.md
Format
# API Skills
## Create User
Create a new user account
**Function:** `createUser`
**Parameters:**
- `email` (string, required) - User email address
- `name` (string, required) - Full name
- `password` (string, required) - Password (min 8 chars)
**Returns:** User object with ID and timestamps
**Example:**
```json
{
"email": "user@example.com",
"name": "John Doe",
"password": "SecurePass123"
}
Response:
{
"id": "usr_abc123",
"email": "user@example.com",
"name": "John Doe",
"created_at": "2024-01-15T10:30:00Z"
}
List Users
Retrieve paginated list of users
Function: listUsers
Parameters:
page(number, optional) - Page number (default: 1)limit(number, optional) - Items per page (default: 10)sort(string, optional) - Sort field (default: created_at)
Returns: Array of user objects with pagination metadata
### Configuration
Customize skill.md generation:
```json
{
"ai": {
"skillMd": {
"enabled": true,
"includeExamples": true,
"includeErrors": true,
"format": "agent-ready"
}
}
}
Use Cases
AI Agents:
- Claude Code, Cursor, Windsurf
- Auto-discover API capabilities
- Generate correct API calls
- Handle errors appropriately
Documentation Tools:
- Auto-complete in IDEs
- API client generation
- Testing frameworks
MCP (Model Context Protocol)
Expose documentation through Model Context Protocol for AI tools.
What is MCP?
Protocol that allows AI tools to access and interact with documentation:
- Standardized interface
- Real-time doc access
- Function calling support
- Resource discovery
Configuration
Enable MCP in docs.json:
{
"contextual": {
"options": ["mcp"]
},
"ai": {
"mcp": {
"enabled": true,
"endpoint": "/mcp",
"capabilities": ["read", "search", "navigate"]
}
}
}
MCP Capabilities
Resources:
- List all documentation pages
- Read page content
- Access metadata
Search:
- Full-text search
- Semantic search
- Filter by section
Navigation:
- Get navigation structure
- Find related pages
- Access breadcrumbs
MCP Client Integration
Claude Desktop:
{
"mcpServers": {
"docs": {
"url": "https://docs.example.com/mcp",
"apiKey": "optional-key"
}
}
}
VSCode with Continue:
{
"contextProviders": [
{
"name": "docs",
"type": "mcp",
"url": "https://docs.example.com/mcp"
}
]
}
Contextual Menu Options
Quick access to AI tools from documentation pages.
Configuration
{
"contextual": {
"options": [
"copy",
"view",
"chatgpt",
"claude",
"perplexity",
"mcp",
"cursor",
"vscode"
]
}
}
Available Options
copy - Copy page content to clipboard
Copies: Markdown content with frontmatter
Use: Paste into any editor or tool
view - View raw markdown source
Opens: Raw .mdx file content
Use: See exact markdown structure
chatgpt - Open in ChatGPT
Action: Opens ChatGPT with page context
Prompt: "Explain this documentation: [content]"
claude - Open in Claude
Action: Opens Claude.ai with page context
Prompt: "Help me understand: [content]"
perplexity - Open in Perplexity
Action: Search Perplexity with page topic
Query: Key concepts from page
mcp - Copy MCP resource URI
Copies: MCP resource identifier
Use: Reference in MCP-enabled tools
cursor - Open in Cursor editor
Action: cursor://open?url=[page-url]
Use: Edit in Cursor IDE
vscode - Open in VS Code
Action: vscode://file/[local-path]
Use: Edit in VS Code
Custom Options
Add custom contextual menu items:
{
"contextual": {
"custom": [
{
"name": "Open in Notion",
"icon": "notion",
"url": "https://notion.so/import?url={pageUrl}"
},
{
"name": "Translate",
"icon": "language",
"url": "https://translate.google.com/?text={content}"
}
]
}
}
Discord Bot
AI-powered Discord bot for documentation queries.
Setup
-
Enable Bot:
- Go to Mintlify dashboard
- Navigate to Integrations > Discord
- Click "Enable Discord Bot"
-
Add to Server:
- Copy bot invite URL
- Open in browser
- Select Discord server
- Authorize permissions
-
Configure:
{ "integrations": { "discord": { "enabled": true, "channelIds": ["123456789", "987654321"], "prefix": "!docs", "permissions": ["read", "search"] } } }
Usage
Search Documentation:
!docs search authentication
!docs how to create API key
!docs what is rate limiting
Get Page:
!docs page introduction
!docs link api/users
Ask Questions:
!docs What authentication methods are supported?
!docs How do I paginate results?
!docs Show me example of creating a user
Bot Features
- Natural language search
- Code example formatting
- Inline documentation links
- Contextual answers
- Source citations
- Slash commands support
Slack Bot
AI assistant for Slack workspaces.
Setup
-
Enable Integration:
- Go to Mintlify dashboard
- Navigate to Integrations > Slack
- Click "Add to Slack"
-
Authorize:
- Select workspace
- Approve permissions
- Configure channels
-
Configuration:
{ "integrations": { "slack": { "enabled": true, "channels": ["#engineering", "#support"], "notifyUpdates": true, "dailyDigest": true } } }
Usage
Ask Questions:
@DocsBot How do I authenticate API requests?
@DocsBot Show me user creation example
@DocsBot What's the rate limit for /users endpoint?
Search:
/docs search webhooks
/docs find deployment guide
Get Updates:
/docs subscribe api-updates
/docs notifications on
Features
- Conversational interface
- Code snippet formatting
- Direct message support
- Channel subscriptions
- Documentation update notifications
- Daily digest summaries
Agent Automation
AI agent for automated documentation tasks.
Configuration
{
"ai": {
"agent": {
"enabled": true,
"capabilities": [
"suggest-improvements",
"detect-outdated",
"generate-examples",
"fix-broken-links"
],
"schedule": "daily",
"notifications": {
"slack": "#docs-updates",
"email": "team@example.com"
}
}
}
}
Capabilities
Suggest Improvements:
- Identify unclear explanations
- Suggest better wording
- Recommend additional examples
- Highlight missing sections
Detect Outdated Content:
- Compare with codebase
- Check API version compatibility
- Flag deprecated features
- Identify stale examples
Generate Examples:
- Auto-generate code examples
- Create usage scenarios
- Build tutorial content
- Produce troubleshooting guides
Fix Broken Links:
- Scan for 404s
- Update redirected URLs
- Fix internal references
- Validate external links
Slack Integration
Receive agent suggestions in Slack:
Agent Report - Daily Digest
Suggestions (3):
- Add Python example to /api/authentication
- Update rate limits in /api/overview (changed in v2.5)
- Clarify webhook signature verification in /webhooks
Broken Links (1):
- /guides/deployment links to removed page /setup
Outdated Content (2):
- /api/users references deprecated `user_type` field
- /quickstart shows old authentication method
Workflow Automation
Configure automated workflows:
{
"ai": {
"workflows": [
{
"name": "Weekly Review",
"trigger": "schedule",
"schedule": "0 9 * * MON",
"actions": [
"detect-outdated",
"broken-links",
"suggest-improvements"
],
"output": "slack"
},
{
"name": "PR Review",
"trigger": "pull_request",
"actions": [
"validate-changes",
"suggest-examples",
"check-consistency"
],
"output": "github"
}
]
}
}
AI API Access
Programmatic access to AI features.
Endpoints
Search:
curl -X POST https://api.mintlify.com/v1/ai/search \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "How do I authenticate?",
"scope": "api"
}'
Ask Question:
curl -X POST https://api.mintlify.com/v1/ai/ask \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"question": "What are the rate limits?",
"context": ["api/overview", "api/rate-limits"]
}'
Generate Example:
curl -X POST https://api.mintlify.com/v1/ai/generate \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"type": "code_example",
"endpoint": "POST /users",
"language": "python"
}'
SDK Usage
JavaScript:
import { MintlifyAI } from '@mintlify/ai';
const ai = new MintlifyAI({ apiKey: 'YOUR_API_KEY' });
const answer = await ai.ask({
question: 'How do I authenticate API requests?',
context: ['api/authentication']
});
console.log(answer.response);
console.log(answer.sources);
Python:
from mintlify import MintlifyAI
ai = MintlifyAI(api_key='YOUR_API_KEY')
answer = ai.ask(
question='How do I authenticate API requests?',
context=['api/authentication']
)
print(answer.response)
print(answer.sources)
Analytics and Insights
Track AI feature usage and effectiveness.
AI Metrics
Search Analytics:
- Popular queries
- Query success rate
- Zero-result searches
- Click-through rates
Question Analytics:
- Most asked questions
- Response accuracy
- User satisfaction ratings
- Follow-up questions
Usage Patterns:
- Peak usage times
- User segments
- Feature adoption
- Integration usage
Dashboard
View AI analytics in Mintlify dashboard:
- AI > Analytics
- Filter by date range
- Export reports
- Track trends
Configuration
{
"ai": {
"analytics": {
"enabled": true,
"trackQueries": true,
"trackClicks": true,
"collectFeedback": true
}
}
}