Wolai MCP. Turn raw data into structured, accessible knowledge articles.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Wolai lets your AI agent manage all company knowledge, combining wiki-style pages with structured databases. Forget clicking through complex menus; you simply ask for information or tell it to build new documentation using natural conversation.
It’s an automated system for organizing everything from meeting notes to product roadmaps.
What your AI agents can do
Create database row
Adds a brand new, fully populated row of data into the database you specify.
Create page
Generates and publishes an entirely new page within your Wolai workspace.
Get database
Returns the schema and structure of a chosen database.
Reads and reports every page available in your knowledge base.
Retrieves the full content and metadata for one designated page.
Runs complex searches against your defined databases to pull out precise facts.
Adds a complete, formatted row of data into an existing database table.
Accesses the raw text and media information inside any given page.
Shows a list of all structured data repositories in your workspace.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Wolai: 10 Tools for Knowledge Management
These tools allow your agent to read the structure of your workspace, query raw data in databases, and build out entirely new pages of 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 Wolai on Vinkius019d849ecreate database row
Adds a brand new, fully populated row of data into the database you specify.
019d849ecreate page
Generates and publishes an entirely new page within your Wolai workspace.
019d849eget database
Returns the schema and structure of a chosen database.
019d849eget page
Fetches the complete details and metadata for a single specified page.
019d849eget workspace info
Pulls high-level information about your entire knowledge base structure and configuration.
019d849elist blocks
Shows all individual content blocks within a specific page for detailed review.
019d849elist databases
Lists every structured database available in your workspace.
019d849elist pages
Retrieves a list of all primary content pages in your workspace.
019d849elist users
Retrieves a list of all accounts that are part of the collaborative workspace.
019d849equery database
Runs targeted searches against your structured databases to find data rows that match 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 Wolai, then connect any of our 4,900+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,900+ 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 Wolai. 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.
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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.
The manual effort of keeping documentation current kills productivity.
Today, updating your knowledge base means navigating ten different menus: checking the database, finding the right page, opening the content block viewer, and then manually copying data points into a new document. It’s hours of clicking through tabs just to consolidate one simple report.
With this MCP, you simply tell your agent what needs documenting. It handles the complex calls behind the scenes. You get back a newly created page with fully populated sections, ready for review.
Get structured data and turn it into actionable knowledge using Wolai.
You no longer have to manually query multiple sources. The agent uses list_databases to map out what exists, queries the needed information via query_database, and then uses create_page to publish a final, clean document with minimal human intervention.
The difference now is that your documentation process shifts from 'data gathering' to 'curation.' You focus on structure; the agent handles the retrieval.
What you can do with this MCP connector
Wolai handles the chaos of massive internal knowledge bases. Instead of wrestling with a complicated web interface just to find one fact, your agent treats your workspace like a unified intelligence layer. It can instantly list all accessible pages and retrieve deep details about specific content blocks within those pages.
Need to track feature requirements? The system manages multi-dimensional databases; you can query them or even create brand new records without touching the UI. This ability to treat raw data as the source for structured documentation is a huge deal. When your agent runs on Vinkius, it means that even if you build complex workflows combining Wolai with other services (like a CRM or billing MCP), everything passes through a zero-trust proxy.
Your keys never sit on a disk; they only move in transit. This keeps the entire documentation process secure while allowing you to automate processes across multiple platforms.
019d849e-bb94-70aa-82ae-8f9578a497c3 
How Wolai MCP Works
- 1 Subscribe to the Wolai MCP and provide your required App ID and Secret credentials.
- 2 Connect your preferred AI client, like Claude or Cursor, through the Vinkius platform.
- 3 Direct your agent with a request—for instance, 'List all pages related to Q3 planning'—and it executes the necessary steps.
The bottom line is you talk to your knowledge base using natural language, and the MCP handles the complex calls behind the scenes.
Who Is Wolai MCP For?
Technical writers who are sick of manually copying data from spreadsheets into wikis. Product managers constantly cross-referencing feature requirements across multiple documents. Operations analysts needing a single source of truth for team knowledge.
Uses the agent to query product backlogs and synthesize findings into draft requirement pages.
Asks the system to find all related documentation blocks for a new feature, then compiles them into a single guide using create_page.
Checks the list of users and pages to audit who has access to sensitive team databases.
What Changes When You Connect
- Stop manually compiling docs. Instead of copy-pasting facts from a spreadsheet to a wiki page, use query_database and let your agent pull the precise data needed for the article.
- Build out documentation on demand. When you need a new guide or project kickoff document, simply ask the system to create_page; it handles the setup and publishing process.
- Deep dive into content. If you only know the page title, list_blocks allows your agent to look inside and find specific pieces of media or text without needing the full context.
- Understand your data structure. Use get_database to see exactly what fields are available before attempting to query it, preventing failed searches down the line.
- Audit team access easily. The list_users tool lets you check who has permission to view and edit core knowledge areas, which is key for compliance checks.
Real-World Use Cases
Project requirements are scattered everywhere.
A PM needs to gather all high-priority feature requests. They ask the agent to query_database on 'Product Backlog' and then synthesize those results, using get_page to draft a summary document for stakeholders.
The team wiki is outdated.
A technical writer needs to update the main onboarding guide. First, they call list_pages to see all related content areas, then use create_page to build the new version and populate it with blocks from existing sources.
I need a report on who can access sensitive data.
An operations analyst uses list_users in combination with get_workspace_info to quickly map out team roles and determine if all collaborators have the necessary permissions for the most critical databases.
I don't know where the original specs are.
A researcher asks the agent to list_pages, gets a directory of potential documents, selects one via get_page, and then uses list_blocks to find the specific section detailing API endpoints.
The Tradeoffs
Treating it like simple search.
Asking the agent, 'Tell me about X' without providing context. The system doesn't know which database or page to look at first and will fail or give generic answers.
→ Always scope your request. Start by calling list_pages to narrow down the scope, then use get_page on a specific ID before asking for details.
Manual data compilation.
Copying key metrics from a spreadsheet and pasting them into a wiki page because it seems faster than documentation.
→ Use query_database to pull the exact metric you need, then use create_page to build the guide around that structured output. Don't copy; let the agent extract.
Over-relying on one source of truth.
Assuming all project data lives in a single document when it might be spread across multiple databases and pages.
→ Use list_databases first to see the full scope. Then, query_database for structured facts and use get_workspace_info to map relationships between those sources.
When It Fits, When It Doesn't
Use this MCP if your core problem involves moving information from a raw state (like a spreadsheet or database) into a usable, organized document structure. You should use it when you need the AI agent not only to read data but also to create new content based on that data. Don't use it if your goal is simple Q&A—if all you need is to ask general questions and get summarized text without needing to write or update documentation, a pure Retrieval Augmented Generation (RAG) tool might be better suited. However, if you need to query structured facts using query_database, and then immediately turn those facts into a polished guide using create_page, this MCP is exactly what you need.
Common Questions About Wolai MCP
How do I find my Wolai App ID and Secret? +
Log in to Wolai, go to [Personal Center] → [Space Settings] → [App Settings], and create a 'Self-built App' to generate your App ID and App Secret.
Can I search for specific data within a database? +
Yes. Use the query_database tool with the database ID. You can optionally provide a JSON filter string to narrow down the results based on your criteria.
What is a 'Block' in Wolai? +
Like Notion, Wolai uses a block-based structure. Everything from a paragraph of text to an image or a sub-page is considered a block. You can list these using the list_blocks tool.
If I need to understand the fields for a new query, how does `get_database` help me? +
It returns the full database schema. You'll see every column name and data type available before writing a complex query with query_database. This prevents guesswork when structuring your data calls.
After I run `list_pages`, how can I use the page ID to create a new Wolai page with `create_page`? +
You pass the specific Page ID you want to link to. The tool handles creating the structure, ensuring that the newly created content is properly attached and scoped within your existing workspace context.
If I need user data, what does the `list_users` tool provide about team membership? +
It gives a list of all active users in the Wolai workspace. You can use this list to check roles or manage who has access to specific pages and databases. It's essential for tracking collaboration.
When I use `get_page`, what kind of errors should I expect if the provided Page ID isn't valid? +
The tool will return a clear 'Not Found' status code, along with details explaining which specific Page ID is missing or inaccessible. This helps you narrow down where your data structure might be broken.
If I need to see my overall system context, how does `get_workspace_info` work? +
It provides high-level metadata about the entire Wolai environment. This includes global settings and details that frame all your pages and databases, giving you a complete overview.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.