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Quip MCP. Search, read, and edit collaborative docs with AI.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Quip MCP on Cursor AI Code Editor MCP Client Quip MCP on Claude Desktop App MCP Integration Quip MCP on OpenAI Agents SDK MCP Compatible Quip MCP on Visual Studio Code MCP Extension Client Quip MCP on GitHub Copilot AI Agent MCP Integration Quip MCP on Google Gemini AI MCP Integration Quip MCP on Lovable AI Development MCP Client Quip MCP on Mistral AI Agents MCP Compatible Quip MCP on Amazon AWS Bedrock MCP Support

Just plug in your AI agents and start using Vinkius.

Quip connects your AI client directly to Quip, giving it full access to your real-time documents, spreadsheets, and team discussions.

Your agent can search across all threads for specific data points, read document content without leaving your IDE, retrieve attached messages, or programmatically edit sections of any document using HTML payloads.

What your AI agents can do

Edit document

Updates content inside a specific Quip document using an HTML payload you provide.

Get contacts

Lists all people who collaborate with your user account in Quip.

Get current user

Retrieves basic profile information for the user currently logged into Quip.

+ 9 more capabilities included
Search Document Archives

The agent performs full-text searches across all Quip documents to locate specific information.

Retrieve Thread Content

Retrieves the complete text and metadata for a single document or thread using its unique ID.

Check Recent Work History

Lists documents that you or your team have viewed or edited recently, helping you resume work quickly.

Review Attached Discussions

Fetches all chat messages and comments attached to a specific document thread for feedback review.

Programmatic Content Edits

Updates the content of an existing Quip document by accepting structured HTML payloads.

List Embedded Media

Pulls a list of all images and files embedded within a given thread.

Supported MCP Clients

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients
Free for Subscribers

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AI Agent

Quip MCP Server: 12 Tools for Collaboration Ops

These tools let your AI client interact with Quip's core functionality—from searching archives to modifying documents and reviewing comments.

edit019d75fb

edit document

Updates content inside a specific Quip document using an HTML payload you provide.

get019d75fb

get contacts

Lists all people who collaborate with your user account in Quip.

get019d75fb

get current user

Retrieves basic profile information for the user currently logged into Quip.

get019d75fb

get folder

Fetches detailed metadata for a single, specified Quip folder.

get019d75fb

get folders

Retrieves batch details for multiple Quip folders using a comma-separated list of IDs.

get019d75fb

get messages

Lists all chat messages and comments attached to a specific document thread ID.

get019d75fb

get recent threads

Retrieves a list of documents that have been recently viewed or edited by the user.

get019d75fb

get thread

Fetches the full content and metadata for one Quip document/thread ID.

get019d75fb

get threads

Retrieves batch contents for multiple Quip threads using a comma-separated list of IDs.

get019d75fb

get user

Retrieves detailed profile information for any specific user by their ID.

list019d75fb

list blobs

Gets a list of all embedded files and images contained within a document thread.

search019d75fb

search threads

Runs a full-text search across every Quip document you have access to.

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
Start building

Make Your AI Do More

Start with Quip, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 4,700+ 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

What you can do with this MCP connector

Your AI client connects straight to Quip. It gives your agent deep access to everything—your live documents, spreadsheets, and team chats. You don’t have to leave your IDE; you can pull all this info right where you are working.

Search and Discovery

You need information from a mountain of docs? Your agent runs full-text searches across every Quip document you've got access to using the search_threads tool. You can also quickly check what threads you or your team have looked at lately with get_recent_threads. Need to drill down into one specific conversation? You fetch all the content and metadata for any single thread ID with get_thread.

If you're dealing with multiple conversations, you can batch-fetch them using a comma-separated list of IDs via get_threads.

Document Content Management

When you need to work inside the file itself, your agent handles it. You can retrieve detailed metadata for an entire folder by calling get_folder, or grab batch details for multiple folders at once using a list of IDs in get_folders. For specific people, your client pulls basic profile info for the user currently logged in with get_current_user, and it can also pull detailed profiles for any other user if you provide their ID via get_user.

Reading and Reviewing Data

When you need to see what's inside, your agent has options. You get the full content of a single thread using get_thread. If you want to check out all the comments and messages attached to that document—maybe looking for feedback—you use get_messages to list every chat comment tied to a specific thread ID.

Embedded media, like images or files, don't escape your notice either; you pull a complete list of everything embedded in a given thread using list_blobs. You can also get a simple roster of everyone who collaborates with your account by running get_contacts.

Making Changes and Edits

Sometimes, 'reading' isn't enough. Your agent lets you programmatically update an existing Quip document using the edit_document tool. You just provide structured HTML payloads, and your client writes that content directly into a specific Quip document.

How It Works

You authorize this server with your Quip Personal Access Token. Then, you tell your AI client exactly what job it needs to do—'Find all mentions of Q3 revenue in the marketing docs,' or 'Change the date on slide five.' Your agent then picks the right tool, like search_threads or get_messages, runs it against Quip, and hands you the clean data.

It doesn't just find the info; it formats it for you.

How Quip MCP Works

  1. 1 First, you must subscribe to the server and authorize it with your Quip Personal Access Token.
  2. 2 Next, prompt your AI client with a specific request (e.g., 'Find all documents about Q3 marketing').
  3. 3 The agent executes the necessary tools (like search_threads), pulls the data, and presents the final answer.

The bottom line is: you talk to your AI client, and it runs Quip's APIs for you. You never leave your IDE.

Who Is Quip MCP For?

This is for the developer or product manager who gets frustrated by context switching. If your day involves jumping between documentation silos—Jira, Google Docs, Quip—and you're tired of manually copying links and summarizing conversations from disparate sources, this server saves hours. It puts all that collaborative data into your AI client.

Software Developer

Uses search_threads to pull technical specs or PRD text directly from Quip before writing a line of code.

Product Manager

Runs queries on get_messages to summarize recent feedback and comment threads attached to product strategy documents.

Account Executive

Drafts client updates and uses edit_document to push the finished HTML text into a shared Quip document for immediate review.

What Changes When You Connect

  • Instantly find relevant data. Instead of manually sifting through folders, use search_threads to query the entire Quip document library for terms like 'Q3 Roadmap'.
  • Stop context switching. Use get_thread and get_folders to pull specific documents into your IDE context without leaving the window.
  • Keep feedback centralized. Run get_messages on a thread ID to pull all attached comments, so you don't miss client feedback buried in chat history.
  • Update content directly. When you finish drafting an update, use edit_document to push the final HTML text straight into the shared Quip document.
  • See what was last touched. get_recent_threads gives you a quick list of documents that need review or follow-up, saving you from manual folder checks.

Real-World Use Cases

01

Drafting Client Status Reports

An Account Executive needs to update a client document. They use search_threads first to pull the latest meeting notes on the project. Then, they structure those notes and use edit_document to write the final section into the shared Quip report.

02

Pulling Code Context from Specs

A Developer starts a new feature branch. They realize they need the latest PRD details. They prompt their agent, which runs search_threads for 'Feature X specs,' retrieving the necessary technical requirements into their IDE before writing any code.

03

Summarizing Product Feedback

A Product Manager needs to know what people think about a new feature. They use get_messages on the feature's main thread ID, getting all attached comments and summarizing them in one go instead of reading dozens of individual messages.

04

Building an Internal Knowledge Base

A researcher needs to compile a report. They use get_folders to list the relevant department folders, then iterate through those IDs using get_threads to retrieve and consolidate key documents into one place.

The Tradeoffs

Trying to edit text manually

The user tries to tell the agent: 'Change this paragraph in ABC123DEF to say X.' The system fails because it doesn't know how to structure the content.

Always use edit_document and provide the payload as a full HTML block. Don't just send raw text; wrap your changes in proper tags like <p>...</p>.

Assuming documents are siloed

The user only looks at the 'Marketing' folder and assumes all project documentation lives there, missing specs stored elsewhere.

Start with search_threads. It searches across all accessible Quip content. This is how you guarantee you find everything.

Ignoring collaboration context

The user gets the document content via get_thread but misses the latest feedback from a team member who commented hours later.

Always run get_messages immediately after retrieving the thread. This ensures you capture all recent comments and discussion points.

When It Fits, When It Doesn't

Use this Quip server if your primary pain point is accessing, querying, or modifying content within real-time collaborative documents (e.g., specs, roadmaps, client drafts). The key strength here is the ability to treat a document's conversation history (get_messages) and its written content (get_thread) as one unified data source.

Don't use this if your goal is managing structured databases outside of Quip (like customer billing records or inventory counts); for that, look at specialized database connector tools. Also, don't rely on it for high-frequency, real-time event streams; stick to the content retrieval and modification tools like edit_document and search_threads. It excels at knowledge extraction from human collaboration.

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Quip. 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

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Managed infra

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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

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Token Compression

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How we secure it →

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 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Available Capabilities

edit_document get_contacts get_current_user get_folder get_folders get_messages get_recent_threads get_thread get_threads get_user list_blobs search_threads

Finding a single piece of information shouldn't take 20 clicks across four different tabs.

Today, finding the right info means clicking into the main folder, checking the thread list, opening the document, and then scrolling through attachments or comments. You end up copy-pasting three separate pieces of data just to summarize one concept.

With Quip MCP, you ask your agent a question—like 'What did Sarah say about the budget last week?'—and it runs `search_threads` and `get_messages`. It gives you the direct answer without you ever leaving your IDE.

The Quip MCP Server allows you to update content with `edit_document`.

Before this, if you needed to fix a typo or add a section to a shared document, someone had to manually open the file and make the change. You were limited to viewing; making changes was clunky and required multiple steps.

Now, your agent executes `edit_document` using an HTML payload. It's direct. The content gets updated instantly in the source Quip thread. No manual steps are needed—just a prompt.

Common Questions About Quip MCP

How do I securely obtain my Quip Access Token? +

Sign in to your Quip account. Navigate to your API token generator page (usually at platform.quip.com or via Quip's Developer Settings). Generate a Personal Access Token, copy the string, and securely save it in the configuration fields below.

Can I provide a Quip document URL to my AI, or just the ID? +

You can provide the standard URL. The agent is capable of recognizing the URL structure, extracting the alphanumeric thread_id, and performing the operation accurately.

Can it read embedded images or files inside the document? +

The agent detects their existence by reading the raw structure and uses list_blobs to catalog attachments. However, downloading the actual files depends on your client's supported capabilities.

Is the edit operation destructive? +

The edit_document function uses Quip's native append logic to add new HTML blocks at the end of the document, mitigating complete overwrites. Additionally, Quip maintains a full version history allowing rollbacks if necessary.

How does using `get_messages` differ from retrieving the full content of a thread using `get_thread`? +

The get_messages tool retrieves only the comments and feedback attached to a specific document or thread. It does not pull the core, main body text of the Quip document itself. This makes it ideal for summarizing discussion points without needing the entire document context.

What kind of user details can I retrieve using the `get_current_user` tool? +

It retrieves your authenticated profile information within Quip, including basic details like display name and email address. This allows your AI client to understand who is operating the agent without needing separate lookups.

When I use the `edit_document` tool, must the content I pass be in HTML format? +

Yes, you must provide the new content as an HTML payload. The Quip API requires this structured markup to correctly append headings, paragraphs, and other formatting elements back into the document thread.

Can I use `get_folders` for large numbers of IDs, and are there limits? +

While you can pass a comma-separated list of many folder IDs, be mindful of API rate limits. If your request exceeds the maximum batch size, the AI client will handle pagination or require splitting your ID list into smaller chunks.

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Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients

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