ButterCMS MCP. Audit all your site's content structure via AI.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
ButterCMS MCP connects your AI agent directly into a headless CMS, letting you read and map all site content—from blog posts to custom collections—through natural conversation.
It lets developers audit tag structures, extract specific page data, or run full-text searches across the entire knowledge base without touching the API console.
What your AI agents can do
Get page layout
Retrieves the exact structural blueprint of any specific page on the site.
Get post details
Pulls all detailed information for an article using its unique identifier (slug).
List blog posts
Identifies the set of available blog posts within the CMS system.
Find specific articles or gather knowledge by searching full-text indexes across your blog.
Examine all configured tags, authors, and categories in a single operation.
Enumerate every existing collection or custom page structure on the site.
Retrieve all structural data for a single post using its unique slug.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
ButterCMS: 10 Tools for Content Structure
These tools give your agent granular control over every piece of metadata in the CMS, letting you enumerate collections, search posts, and analyze taxonomy structures.
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 ButterCMS on Vinkius019d7566get page layout
Retrieves the exact structural blueprint of any specific page on the site.
019d7566get post details
Pulls all detailed information for an article using its unique identifier (slug).
019d7566list blog posts
Identifies the set of available blog posts within the CMS system.
019d7566list butter authors
Retrieves a list of all authors who have contributed content to the site.
019d7566list butter categories
Analyzes and lists every major content category defined in the CMS structure.
019d7566list butter tags
Maps all global tags used across your entire site's content.
019d7566list custom pages
Inspects and lists deep, structured arrays detailing specific custom page setups.
019d7566list global collections
Enumerates all explicitly defined content collections available for use.
019d7566search blog posts
Performs a full-text search across blog posts using keywords or phrases.
019d7566search collection field
Finds specific data points within filtered content collections based on criteria.
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 ButterCMS, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ 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 ButterCMS. 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
Works with 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 server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Dealing with content data feels like digging through dusty server logs.
Today, getting a full picture of your site’s knowledge base requires switching between the CMS dashboard, running multiple reports, and manually cross-referencing tag lists. You copy dozens of slugs just to feed them into an analysis tool—a process that takes forever.
With this MCP, you ask your agent what you need. It uses tools like `list_butter_categories` or `search_blog_posts` to pull the entire structure and data set automatically. The result is a single, clean block of text containing all the necessary raw information.
Getting Site Structure with list_global_collections
Previously, you had to guess which content types were available and then run separate queries for each one. You'd check the blog feed, then separately check the custom pages, leaving gaps in your inventory.
Now, running `list_global_collections` gives you an immediate, enumerated list of every structured data type on site. It’s a reliable starting point that ensures nothing is missed.
What you can do with this MCP connector
Need to get context from your website's internal structure? This MCP connects any AI agent to a ButterCMS instance, letting you pull rich text and content taxonomy through simple conversations. Instead of navigating a dashboard and copy-pasting data points, your agent explores your entire content warehouse for you. You can gather knowledge by reading precise articles using the slug or running full-text searches across all posts.
The system also handles complex organizational structures; you can list authors, find every existing category, and map raw page models from multiple collections. This eliminates manual database lookups. When you use Vinkius, your agent's actions are tracked in real time via Vinkius AI Analytics, so you always know exactly which content sources were read and how the data flowed through.
019d7566-564e-73f0-bb60-4d88aa4c5501 
How ButterCMS MCP Works
- 1 Subscribe to this MCP and paste your ButterCMS API Token into the Vinkius platform.
- 2 Point your AI agent at this connection. The agent then uses natural language prompts to select which content data it needs (e.g., 'List all authors').
- 3 The agent fetches the structured JSON response, giving you clean, machine-readable data directly in your client.
The bottom line is: you talk to the system like a human asking questions; the MCP translates that into precise API calls and hands back clean, organized content blocks.
Who Is ButterCMS MCP For?
Content teams, SEO specialists, and headless engineers. You're the person who spends hours clicking through CMS interfaces just to gather a list of tags or check if two pieces of content talk about the same topic. This MCP gives your agent instant access.
You need to quickly audit existing tag structures and locate all articles written by a specific author to propose backlink opportunities.
You're debugging component hits, needing to identify why certain custom page configurations aren't outputting the expected nested JSON data.
You want a rapid scan to confirm if an article covering a target keyword already exists in the official knowledge base before writing anything new.
What Changes When You Connect
- Stop manual auditing. You can use
list_butter_tagsandlist_butter_categoriesto map out every single taxonomy group in seconds, replacing hours of console clicking. - Need context on a specific article? Instead of guessing the URL, run
get_post_detailswith just the slug to pull all associated metadata, authors, and body text instantly. - Build cross-platform automations. You can combine this MCP with other tools in your agent's workflow—say, taking data from a collection using
list_global_collectionsand feeding it into an email drafting tool. - Debug component architecture easily. If a custom page isn't rendering right, use
get_page_layoutto pull the exact structural blueprint needed for debugging. - Find knowledge gaps fast. Run a deep search using
search_blog_poststo check if critical keywords are already covered by existing articles.
Real-World Use Cases
Performing an SEO Audit
An SEO manager wants to see which authors wrote about 'AI agents' and what related topics they touched. They ask the agent to use list_butter_authors first, then search for posts using search_blog_posts, effectively creating a report on content clusters.
Debugging Page Rendering
A developer notices a custom page is missing fields. They run the agent to use list_custom_pages to see the available structure, then call get_page_layout to verify that specific component's required JSON output.
Discovering Content Scope
A content team needs a full inventory of all potential topics. They ask for the list of categories (list_butter_categories) and collections (list_global_collections), getting a comprehensive overview in one flow.
The Tradeoffs
Trying to search everything at once
Asking the agent, 'Give me all content about AI.' This is too vague and forces the system to guess which tools are needed.
→
Break it down. First, run list_global_collections to define scope. Then, use search_blog_posts with a precise query like 'LLM frameworks' for better results.
Ignoring content types
Only running basic searches and missing highly structured data held in custom pages.
→
Always check the specialized tools. You must explicitly use list_custom_pages and search_collection_field to see that complex, organized data.
Asking for a 'graph' view
The agent cannot magically draw connections between every article and collection; it only reads structured data.
→
You have to build the graph yourself. Run list_butter_tags to get all tags, then run multiple searches using those tags as filters.
When It Fits, When It Doesn't
Use this MCP if your primary problem is reading, auditing, or structuring content that lives inside ButterCMS. Think: 'I need the raw data from my published articles.' Don't use it if your goal is something external to the CMS, like managing user passwords, sending emails outside of a dedicated messaging service, or updating records in an accounting system—for those, you need a different MCP altogether. If you just need a list of posts and tags, this is perfect; if you need to perform an action (like 'publish' or 'edit'), look for a write-access tool instead.
Common Questions About ButterCMS MCP
Can my AI analyze the full content of an already published article? +
Absolutely. Through the generic get_post_details tool using a targeted URL slug, the agent actively retrieves the article content boundaries directly from ButterCMS, letting you check formatting errors inside the markup natively.
Does it connect out to our Custom Pages or specifically built Collections? +
Yes. Beyond just basic blog articles, the agent explores specific array bounds pulling the 'list_custom_pages' endpoint isolating pure localized architectures and fields.
Will it discover writers or tags independently mapping cross-relations? +
Yes! Running standard category lists returns an exact enumeration mapping taxonomy arrays straight into conversational strings. Ask the bot 'Who are our CMS authors?' and watch the results.
How do I connect my credentials before running `get_post_details`? +
You must pass your ButterCMS API Token in the request header. This token authenticates your agent's connection and ensures that only authorized calls can retrieve specific post slugs.
If I use `list_blog_posts`, how does it handle large content arrays? +
The MCP is optimized for bulk data retrieval. It automatically handles pagination, allowing your agent to pull massive sets of posts without hitting rate limits or needing manual page number adjustments.
What is the purpose of running `get_page_layout`? +
This tool retrieves the exact structural matching for a given UI route. Use it when you need to debug component structures and verify how content should be rendered across different website layers.
Can I filter my results using `search_collection_field`? +
Yes, this tool lets your agent identify precise arrays by applying filters to structured rules. You simply pass the required criteria to narrow down content within a specific collection type.
When I run `list_butter_authors`, what details about each CMS Writer do I get? +
It provides an automated validation check for every writer account. You'll receive core metadata, including the author's name and a count of articles they have published.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.