How to Use the Linkup (AI Search & RAG) MCP in AutoGen

Q: How do I hook up Linkup (AI Search & RAG) to my AutoGen agents?

Install autogen-extmcp and use the mcpservertools helper with your Vinkius URL. Pass the resulting tool list directly to your AssistantAgent constructor to give them search capabilities.

Equip your AutoGen multi-agent teams with real-time web search and automated scraping to resolve complex debates.

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Connect Linkup (AI Search & RAG) MCP to AutoGen

Create your Vinkius account to connect Linkup (AI Search & RAG) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Linkup (AI Search & RAG) with AutoGen

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Perplexity

Resolve agent debates with real-time web facts

Your AutoGen agents can verify claims in real time by triggering the `search_web` tool during their debates. AutoGen shines when agents challenge each other's assumptions. Fresh data settles arguments before they derail your workflow. This consensus-driven approach cuts down on logical errors. Your agents negotiate the truth by pulling fresh data, making the final output much more reliable.

Feed clean, scraped data to your AutoGen specialists

To avoid feeding messy HTML to your agents, `fetch_url` extracts clean markdown from complex JavaScript sites. Don't force your specialized agents to read raw HTML. They get the actual page content without the tracking scripts and layout noise. This MCP tool strips the clutter on our secure servers. Your performance agents can quickly scan the clean text, while security agents check it for risks.

Configure search depth for AutoGen workflows

By configuring `search_web` to run in fast or deep mode, you keep your AutoGen conversation loops highly responsive. In an AutoGen setup, some agents only need quick facts while others write deep reports. You control the depth of research on a per-agent basis. This prevents your multi-agent loops from stalling. You keep the fast agents fast and let the research agents take their time gathering deep web context.

Setup guide

Set up Linkup (AI Search & RAG) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Linkup (AI Search & RAG) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Linkup (AI Search & RAG)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Linkup (AI Search & RAG) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Linkup (AI Search & RAG)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Linkup (AI Search & RAG) data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Linkup. 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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Common questions about Linkup (AI Search & RAG) MCP in AutoGen

Install autogen-ext[mcp] and use the mcp_server_tools helper with your Vinkius URL. Pass the resulting tool list directly to your AssistantAgent constructor to give them search capabilities.

Yes. A search specialist agent can call the search tool to find links, then pass those URLs to a scraper agent that uses the fetch tool to read the full pages. They coordinate the work naturally through conversation.

Yes. The Vinkius deployment supports both stdio and streamable HTTP, allowing your AutoGen agents to connect reliably even in distributed, multi-container environments.

The McpToolAdapter in the AutoGen extension handles the schema translation automatically. Your agents will see clean JSON schemas for both search and fetch tools without any manual mapping.

All search queries and scraped web data are processed inside ephemeral, zero-trust sandboxes. Vinkius never logs the content of the pages you fetch or the queries you run, ensuring your multi-agent discussions remain entirely confidential.

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