Bring Wiki
to LlamaIndex
Create your Vinkius account to connect Slab to LlamaIndex and start using all 12 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Slab MCP Server?
Connect your Slab workspace to any AI agent and empower your team to search, read, and write documentation seamlessly. Interact with your organization's entire knowledge base through natural language without ever switching tabs.
What you can do
- Deep Search & Retrieval — Execute full-text searches across all Slab posts to fetch answers, guidelines, and protocols instantly
- Documentation Authoring — Create new articles, meeting notes, or project specs in Markdown, and update existing posts on the fly
- Information Architecture — Browse all your topics (folders) to understand how the company wiki is structured and fetch categorized articles
- Activity Feeds — Pull the most recently updated posts to stay on top of new company policies and documentation changes
- Team Discovery — Retrieve organization metadata and list all registered team members
How it works
- Subscribe to this server
- Enter your Slab Access Token
- Start using Claude, Cursor, or any MCP-compatible client to query your company's collective brain
Stop interrupting engineers to ask where a specific document lives. Your AI agent can read the internal wiki and answer questions directly based on your approved Slab content.
Who is this for?
- Software Developers — pull API documentation or architectural guidelines directly into your IDE while coding
- Product Managers — instantly draft and publish feature specifications or release notes to the right Slab topic
- Onboarding & HR — ask your assistant to fetch the latest company policies or generate reading lists for new hires
Built-in capabilities (12)
This action is irreversible via API. Archive an existing Slab post
Provide content in Markdown. Create a new wiki post in Slab
Create a new topic in Slab to organize posts
Retrieve the Slab organization profile
Retrieve the full content and metadata of a specific Slab post
Retrieve details and list of posts for a specific Slab topic
Returns post IDs and titles. List all wiki posts/articles in the Slab workspace
List the most recently updated posts
List all topics organizing posts in the Slab workspace
List all members of the Slab organization
Full-text search across all Slab posts
Update an existing Slab post title or content
Why LlamaIndex?
LlamaIndex agents combine Slab tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Slab tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Slab tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Slab, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Slab tools were called, what data was returned, and how it influenced the final answer
Slab in LlamaIndex
Why run Slab with Vinkius?
The Slab connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 12 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Slab using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Slab and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Slab to LlamaIndex through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Slab for LlamaIndex
Every request between LlamaIndex and Slab is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
Can my AI use existing wiki guidelines to write new code or copy?
Absolutely. You can request your agent to 'search the Slab wiki for our Frontend Coding Standards' or 'find our Brand Voice Guidelines'. The agent will retrieve the exact Markdown content of those articles and use them as system instructions for the rest of your conversation.
How do I easily publish my AI chat output back to Slab?
When your AI agent generates a good technical specification or summary, simply tell it: 'Create a new post in Slab called [Name], using this entire response as the content, and place it in the Engineering topic.' The agent will format the Markdown and publish it immediately through the create_post tool.
Can my agent clean up outdated company documentation?
Yes. If an article is deprecated, you can tell your AI: 'Archive the post with ID XYZ' or 'Find the old setup guide and archive it.' The agent can execute the archive_post command to hide outdated information and keep your knowledge base pristine.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Slab tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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