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Can my agent clean up outdated company documentation?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 The agent can execute the `archive_post` command to hide outdated information and keep your knowledge base pristine.

Slab MCP Server for AutoGen 12 tools — connect in under 2 minutes

Name: Slab
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 12 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Slab as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="slab_agent",
            tools=tools,
            system_message=(
                "You help users with Slab. "
                "12 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About 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.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Slab tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

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

The Slab MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Slab to AutoGen via MCP

Follow these steps to integrate the Slab MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 12 tools from Slab automatically

Why Use AutoGen with the Slab MCP Server

AutoGen provides unique advantages when paired with Slab through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Slab tools to solve complex tasks

Role-based architecture lets you assign Slab tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Slab tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Slab tool responses in an isolated environment

Slab + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Slab MCP Server delivers measurable value.

Collaborative analysis: one agent queries Slab while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Slab, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Slab data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Slab responses in a sandboxed execution environment

Slab MCP Tools for AutoGen (12)

These 12 tools become available when you connect Slab to AutoGen via MCP:

archive_post

This action is irreversible via API. Archive an existing Slab post

create_post

Provide content in Markdown. Create a new wiki post in Slab

create_topic

Create a new topic in Slab to organize posts

get_organization

Retrieve the Slab organization profile

get_post_details

Retrieve the full content and metadata of a specific Slab post

get_topic_details

Retrieve details and list of posts for a specific Slab topic

list_posts

Returns post IDs and titles. List all wiki posts/articles in the Slab workspace

list_recent_posts

List the most recently updated posts

list_topics

List all topics organizing posts in the Slab workspace

list_users

List all members of the Slab organization

search_posts

Full-text search across all Slab posts

update_post

Update an existing Slab post title or content

Example Prompts for Slab in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Slab immediately.

"Search the Slab wiki for 'VPN Setup Instructions'."

"Create a new topic named 'Q3 Planning' and list the ID so I can save posts to it."

"List the most recent 5 posts updated in the company wiki."

Troubleshooting Slab MCP Server with AutoGen

Common issues when connecting Slab to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Slab + AutoGen FAQ

Common questions about integrating Slab MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Slab tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.