# Slab MCP for AI Agents AI Agent Connect

> Slab MCP lets your AI agent read, write, and search your company wiki. It turns your documentation into an active knowledge base where your agent can fetch guidelines, draft new specs in Markdown, and organize topics without you having to dig through folders manually.

## Overview
- **Category:** knowledge-management
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_IfZmivQXV8XLoMGDXYhcVahnahQo9NcBqGlkU0Ik/ai-agent-connect
- **Tags:** wiki, documentation, knowledge-base, internal-search, team-collaboration

## Description

Imagine your team's collective brain is locked behind a dozen different pages and folders. You want an answer, but you'd rather not spend ten minutes clicking through a wiki to find that one specific security protocol or API endpoint. This Connector opens that door. Instead of hunting for information, you just ask your agent. It can scan your entire Slab workspace to find exactly what you need, whether that's a buried project spec or the latest HR policy. It doesn't just read, though. Your agent can actually do the heavy lifting of drafting new documentation, creating meeting notes in Markdown, and updating existing posts when requirements shift. It handles the tedious parts of information architecture, like creating new topics or archiving old content, so your team's knowledge stays organized. When you use this through the Vinkius catalog, you're basically giving your AI client a seat at the table for your company's internal research. It stops the back-and-forth "where is that document?" messages and lets everyone get back to actual work.

## Tools

### get_organization
Retrieve the Slab organization profile. This provides context about your workspace's basic information.

### list_posts
List all wiki posts in the Slab workspace. Use this to see the full scope of your documentation.

### get_post_details
Retrieve the full content and metadata of a specific Slab post. This lets the agent read the entire article.

### search_posts
Perform a full-text search across all Slab posts. This is the primary way to find specific information quickly.

### list_topics
List all topics organizing posts in the Slab workspace. Use this to understand the high-level wiki structure.

### get_topic_details
Get a list of all posts within a specific Slab topic. This helps the agent understand what's inside a folder.

### list_users
List all members of your Slab organization. This is useful for identifying team members or checking permissions.

### create_post
Create a new wiki post using Markdown content. This allows your agent to draft and publish new documentation.

### update_post
Update an existing Slab post title or content. This lets your agent keep your documentation current as requirements change.

### create_topic
Create a new topic in Slab to organize posts. This helps the agent build out your wiki's folder structure.

### archive_post
Archive an existing Slab post. Use this to keep your active wiki clean and organized.

### list_recent_posts
List the most recently updated posts. This is perfect for seeing what's changed lately.

## Prompt Examples

**Prompt:** 
```
Can you find the guidelines for our remote work policy?
```

**Response:** 
```
I've found the **Remote Work & Hybrid Guidelines** post in your Slab wiki. It covers:

*   **Core hours**: 10am-4pm EST
*   **Equipment**: Stipends for home offices
*   **Communication**: Slack and Zoom expectations

Would you like me to pull the full text for you?
```

**Prompt:** 
```
Create a new topic called 'Q4 Marketing' and put a draft post in it about the holiday campaign.
```

**Response:** 
```
I've created the **Q4 Marketing** topic for you. I also drafted a new post inside it titled **Holiday Campaign Overview**. It includes:

- Campaign goals
- Target audience
- Key dates

Let me know if you want to adjust any of these details.
```

**Prompt:** 
```
What were the most recent updates to our engineering docs?
```

**Response:** 
```
Here are the 3 most recent updates in your Slab workspace:

1. **API Gateway Migration** (Updated 2 hours ago)
2. **Frontend Style Guide** (Updated yesterday)
3. **On-call Rotation Schedule** (Updated Monday)

Would you like me to read the details of any of these?
```

## Capabilities

### Search the entire wiki for specific answers
Your agent scans every post in your workspace to find exact guidelines or protocols.

### Draft and publish new documentation in Markdown
The agent creates new wiki posts with proper headers and formatting from your chat.

### Browse the full structure of your company's topics
Your agent can navigate your folders to understand how the wiki is organized.

### Pull the latest updates to stay current on policies
The agent identifies the most recently edited posts to show you what changed.

### Create and organize new folders for different projects
Your agent builds out your wiki structure by creating new topics for your team.

### Retrieve organization data and team member lists
The agent pulls company metadata and lists of registered team members for you.

## Use Cases

### Finding specific API endpoints
A developer asks the agent to find the auth endpoint. The agent uses `search_posts` and returns the exact Markdown snippet from the wiki.

### Drafting a new PRD
A product manager asks the agent to create a new post in the 'Product Specs' topic. The agent uses `create_post` to draft the requirements.

### Verifying team permissions
An admin asks the agent to list all organization members. The agent uses `list_users` to provide a quick summary of the team.

### Reviewing weekly changes
A manager asks the agent to show what changed in the engineering docs this week. The agent uses `list_recent_posts` to summarize updates.

## Benefits

- Stop searching for links manually by using `search_posts` to find answers instantly.
- Keep documentation fresh by having your agent use `update_post` to modify existing content.
- Draft project specs in seconds with `create_post` which supports full Markdown formatting.
- Maintain a clean wiki structure by using `create_topic` and `archive_post` to organize content.
- Stay updated on company changes by pulling the latest updates with `list_recent_posts`.
- Onboard new hires faster by using `get_post_details` to fetch full policy guides.

## How It Works

The bottom line is your team's wiki becomes a searchable, editable database for your AI agent.

1. Subscribe to this Connector on Vinkius.
2. Paste your Slab Access Token into your AI client settings.
3. Ask your agent to find, write, or organize documentation in your wiki.

## Frequently Asked Questions

**Can the Slab MCP help my team find company policies faster?**
Yes. It allows your agent to perform full-text searches across your entire Slab workspace to find specific guidelines or protocols instantly.

**Can my AI agent actually write new documentation in Slab?**
Yes, it can. Your agent can use the `create_post` tool to draft new articles or project specs in Markdown format directly into your wiki.

**How does the Slab MCP organize my workspace?**
It can create new topics to act as folders and even archive old posts, helping your agent keep your knowledge base structured and clean.

**Can I use this to see who is currently in my Slab organization?**
Yes. Your agent can list all members of your Slab organization to help you identify team members or check permissions.

**Does this Connector work with my existing AI client?**
It works with any MCP-compatible client, including Claude, Cursor, and Windsurf, giving your agent a direct connection to your Slab data.

**Can my agent update existing Slab posts?**
Yes. It can modify both the titles and the content of existing posts, making it easy to keep your documentation current as projects evolve.

**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.