Mintlify MCP for AI. Control your docs lifecycle from chat.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
Mintlify MCP manages and automates your technical documentation lifecycle directly through natural conversation with your AI agent. Check page view analytics, read project configurations, update metadata settings, or trigger full site deployments—all without leaving the chat window.
What AI agents can do with Mintlify Automation
Get metadata
Retrieves the current settings and structural data for your Mintlify project.
Get page views
Fetches page view statistics, allowing you to track documentation traffic over specific periods.
Trigger deployment
Forces a new build and deployment of your entire documentation site immediately.
Retrieve detailed information about your documentation structure and current configuration.
Programmatically change the metadata or settings that control how your documentation is built.
Fetch page view counts and analytics for specific timeframes to gauge user interest.
Force a new deployment of your entire documentation site, useful for CI/CD pipelines.
Ask an AI about this
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What AI agents can do with Mintlify With 4 Tools
Use these tools to read project configurations, track traffic data, modify metadata, and deploy updates for your technical documentation.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Mintlify on VinkiusGet Metadata
Retrieves the current settings and structural data for your Mintlify project.
Get Page Views
Fetches page view statistics, allowing you to track documentation traffic over...
Trigger Deployment
Forces a new build and deployment of your entire documentation site immediately.
Update Metadata
Modifies various settings within the Mintlify project configuration object.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Mintlify, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mintlify. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Keeping Documentation Current Is a Grind, Solved with Vinkius AI Gateway
Right now, updating documentation often feels like a bureaucratic nightmare. You have to remember which dashboard shows the current navigation structure; you need to switch tabs to check page views; and if there's an urgent fix, you spend ten minutes clicking through a complex CI/CD pipeline just to kick off a new build.
With this MCP connection, that process disappears. Instead of clicking, navigating, and copy-pasting between tools, you simply ask your agent to perform the action. You get immediate confirmation—whether it's the analytics data or the deployment status.
Mintlify MCP: Total Control Over Your Documentation
Forget logging in to multiple systems just to verify settings. You can retrieve the entire project structure using `get_metadata` and check traffic performance by calling `get_page_views`, all without ever leaving your chat window.
The result is total control. The agent handles the complexity of API calls, letting you focus only on the content strategy. It's immediate, accurate, and actionable.
What your AI can actually do with this
Use this connection to manage every part of your technical documentation process right from your preferred AI client. Instead of logging into a dashboard, navigating through menus, and copying configuration values, you simply ask your agent what you need done. You can retrieve the current project settings or check how many people viewed a specific guide over the last month.
Need to push out an emergency update? Triggering a full deployment is as simple as asking for it. This MCP makes managing documentation feel like talking to a teammate who already knows where all the buttons are. It works with Vinkius, making this control layer available across every compatible AI client you use.
019ea5f8-68e2-7343-b40d-c3674e1f1a6f Here's how it actually works
The bottom line is: you talk to your agent; it talks to Mintlify.
First, subscribe to the Mintlify MCP and provide your unique API key.
Next, give instructions to your AI client, asking it to perform a specific action, like checking traffic or updating settings.
Your agent executes the command using the necessary tools and returns the requested data—like an analytics report or a success confirmation.
Who is this actually for?
Technical writers, product managers, and developers who hate context switching. If you spend too much time jumping between the documentation dashboard, analytics tools, and code editor just to update a single guide, this MCP is for you.
Uses the agent to inspect navigation structures or verify metadata settings without leaving their writing chat interface.
Quickly checks page view analytics and traffic reports to understand which guides users are actually reading.
Triggers deployments or updates configurations directly from their code editor, fitting into existing CI/CD workflows.
What Changes When You Connect
Stop bouncing between dashboards. You can check page view analytics and project settings—using the get_page_views and get_metadata tools, for example—all within a single conversation with your agent.
Build confidence in your deployments. Instead of manually starting a build process, you tell your agent to use trigger_deployment, ensuring the latest version is always pushed quickly for testing or release.
Fix documentation gaps instantly. If a section needs restructuring, you don't need to log into the admin panel; just ask the agent to update settings using update_metadata and see it happen.
Understand user behavior better. Get immediate insights from traffic data by calling get_page_views, letting you know exactly which guides users spend their time on.
Save hours of context switching. You keep your technical writing flow going; the agent handles the backend API calls for metadata management and deployments.
See it in action
The Docs Rollout Check
A product manager needs to know if a new guide is getting traction. They ask their agent to run get_page_views for the last quarter, instantly showing which pages are gaining momentum and where traffic dropped off.
The Emergency Hotfix
A developer discovers a critical bug in the docs. Instead of following a multi-step CI/CD process, they instruct their agent to use trigger_deployment immediately, getting the fix live within minutes.
Restructuring Content
The technical writer realizes the navigation flow is confusing. They ask the agent to read the current structure using get_metadata, allowing them to revise and then use update_metadata without manual admin access.
Pre-Release Audit
Before a major launch, a developer wants to confirm all project settings are correct. They use the agent to run get_metadata, confirming every required API endpoint and setting is correctly configured.
The honest tradeoffs
Manual Dashboard Monitoring
A PM logs into Mintlify, clicks 'Analytics,' filters by date range (30 days), copies the total view count, and then pastes it into a spreadsheet.
Just tell your agent to use get_page_views for 30 days. It pulls the exact number and delivers it in plain text immediately.
Guessing Deployment Status
A developer finishes code changes but manually waits on a dashboard page, unsure if the build started or failed.
Tell your agent to use trigger_deployment. It executes the command and confirms whether the build started successfully.
Overhauling Settings Blindly
A writer changes documentation settings in the GUI, only to realize they broke a link structure because they didn't know the existing metadata.
Always run get_metadata first. It shows you the full current configuration before you attempt any structural changes with update_metadata.
When It Fits, When It Doesn't
Use this MCP if your pain point is managing the lifecycle of documentation—meaning you need to read structure, change settings, view traffic data, or trigger builds. If you find yourself needing to 'check how many people viewed X' or 'make sure Y setting is enabled,' this is what you need. Don't use it if your goal is simply drafting new content; for that, a standard text generation agent works fine. You only need the Mintlify MCP when the task involves interacting with the platform's backend configuration and deployment process. If all you need to do is write copy and save it locally, skip this connector entirely.
Questions you might have
How do I check page views using Mintlify MCP? +
You call get_page_views. Simply ask your agent for analytics data and specify the time frame you care about. The tool returns a clean summary of traffic, showing total views or specific page counts.
Can I update my documentation settings with Mintlify MCP? +
Yes, use update_metadata. This allows your agent to modify the core configuration object for your project, letting you change things programmatically rather than through a graphical interface.
How do I force a new deployment using Mintlify MCP? +
Use trigger_deployment. You tell your agent to trigger the build. It executes the command and confirms if the latest version is building, which is essential for continuous integration.
What information does get_metadata provide? +
get_metadata retrieves critical data points about your project, including the current navigation structure and key configuration objects needed to understand how Mintlify is built.
We've already built the connector for Mintlify. Just plug in your AI agents and start using Vinkius.
No hosting. No infrastructure. No complex setup.
All 4 tools are live and waiting.
You're up and running in seconds.
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