Can I perform a vector search using float arrays through the agent?

Yes. The `search_near_vector` tool allows you to perform semantic searches by providing a query vector as a JSON array of floats. Your AI agent will return the most similar objects from your Weaviate collection.

How do I see the data structure of my Weaviate collections?

You can use the `get_full_schema` tool to see all classes and properties defined in your instance, or `get_class_schema` if you want to focus on a specific collection's definition.

Is it possible to monitor cluster health via chat?

Absolutely. Use the `get_cluster_nodes` tool to retrieve operational data for all nodes in your Weaviate cluster, including their current status and resource utilization metrics.

Weaviate MCP Server for AutoGen 7 tools — connect in under 2 minutes

Name: Weaviate
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 7 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Weaviate as an MCP tool provider through the 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="weaviate_agent",
            tools=tools,
            system_message=(
                "You help users with Weaviate. "
                "7 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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* 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 Weaviate MCP Server

Connect your Weaviate instance to any AI agent and harness the power of vector search and semantic data management through natural conversation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Weaviate tools. Connect 7 tools through the 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

Semantic Search — Perform nearest neighbor vector similarity searches to find relevant content based on context and meaning
Schema Management — Retrieve the complete instance schema or specific class definitions to understand your data structure
Object Discovery — Browse and list data objects within any class, including full property values and vector data
Deep Data Audit — Retrieve specific data objects by their UUID to inspect metadata and internal configurations
Cluster Monitoring — Monitor operational health, node status, and resource usage of your Weaviate cluster nodes
Instance Metadata — View server version, enabled modules, and high-level configuration details directly from your agent

The Weaviate MCP Server exposes 7 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 Weaviate to AutoGen via MCP

Follow these steps to integrate the Weaviate 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 7 tools from Weaviate automatically

Why Use AutoGen with the Weaviate MCP Server

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

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

Role-based architecture lets you assign Weaviate 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 Weaviate tool calls

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

Weaviate + AutoGen Use Cases

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

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

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

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

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

Weaviate MCP Tools for AutoGen (7)

These 7 tools become available when you connect Weaviate to AutoGen via MCP:

get_class_schema

Retrieves the schema definition for a specific class (collection)

get_cluster_nodes

Retrieves operational information about the Weaviate cluster nodes

get_full_schema

Retrieves the complete Weaviate schema (all collections)

get_instance_metadata

Retrieves metadata about the Weaviate instance

get_object_details

Retrieves a specific data object by its UUID

list_objects

Supports basic pagination via limit. Lists data objects within a specific class

search_near_vector

Provide a class name and a query vector as a JSON array of floats. Performs a nearest neighbor vector similarity search

Example Prompts for Weaviate in AutoGen

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

"List all classes in my Weaviate schema."

"Search the 'Article' class for items similar to this vector: [0.12, -0.05, 0.88, ...]."

"What is the current health status of my Weaviate cluster nodes?"

Troubleshooting Weaviate MCP Server with AutoGen

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

McpWorkbench not found

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

Weaviate + AutoGen FAQ

Common questions about integrating Weaviate 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 Weaviate 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.