How to Use the AddSearch MCP in AutoGen

Q: How do I configure AddSearch for AutoGen?

Run pip install -U autogen-extmcp in your terminal. Use StreamableHttpServerParams to connect to the Vinkius URL and pass the resulting tools to your AssistantAgent.

Q: Can agents use autocomplete?

They have access to the autosuggest tool. This lets them test what users see when typing specific prefixes into your search bar.

Q: How do multiple AutoGen agents share AddSearch results?

One agent executes searchkeyword and posts the raw JSON into the shared conversation context. The other agents read that output and respond based on their system prompts.

Let your AutoGen agents debate search analytics and manage your AddSearch index through consensus using this MCP integration.

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Connect AddSearch MCP to AutoGen

Create your Vinkius account to connect AddSearch 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 AddSearch with AutoGen

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Multi-Agent Search Analytics Review

Data analysis requires multiple perspectives. You can build one AutoGen agent that pulls `stats_queries` to find popular terms, while another agent reviews the list for anomalies. They discuss the findings until they agree on a trend. Once consensus hits, a third agent drafts a report detailing what users actually want.

Negotiate AddSearch Index Updates

Pushing bad data to your live search breaks the customer experience. A drafting agent might propose adding a new FAQ page via `index_document`. Before execution, a compliance agent checks the content against company guidelines. If it spots a violation, it rejects the update and forces the drafter to rewrite it.

Autonomously Prune Dead Content via MCP

Maintaining a clean index is tedious work. Your agent team can run `list_documents` periodically to audit the current database state. When they identify outdated records, they debate whether to archive or delete. If deletion wins out, the executor agent fires `delete_document` to remove the trash.

Setup guide

Set up AddSearch 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 AddSearch 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="AddSearch_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent AddSearch 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="AddSearch_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent AddSearch 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 AddSearch. 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 AddSearch MCP in AutoGen

Run `pip install -U autogen-ext[mcp]` in your terminal. Use `StreamableHttpServerParams` to connect to the Vinkius URL and pass the resulting tools to your `AssistantAgent`.

They have access to the `autosuggest` tool. This lets them test what users see when typing specific prefixes into your search bar.

One agent executes `search_keyword` and posts the raw JSON into the shared conversation context. The other agents read that output and respond based on their system prompts.

You should always require human-in-the-loop approval for destructive actions. Limit access to `delete_document` to a specific MCP client that requires user confirmation.

We handle authentication centrally so you only need one MCP Server endpoint token. Your search queries and click stats pass through a stateless proxy that logs nothing.

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