How to Use the DocsBot MCP in AutoGen

Q: How do AutoGen agents collaborate using DocsBot?

One agent queries the bot using askbotquestion while another audits the source files. They use listbotknowledgesources to verify that the answer is grounded in actual training documents.

Q: How do AutoGen agents track changes in DocsBot?

Agents run listrecentlyindexedbots to monitor updates across your workspace. When a bot gets updated, the agent alerts the rest of the group to refresh their cached knowledge.

Q: Is my DocsBot team workspace data safe with AutoGen?

Your workspace metadata and team bot lists pulled via listteambots are processed locally within the V8 sandbox. The MCP Server handles all authorization protocols locally, meaning no external parties can access your team configuration or API tokens.

Enable multi-agent consensus loops in AutoGen to verify and audit your DocsBot knowledge bases.

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Create your Vinkius account to connect DocsBot 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 DocsBot with AutoGen

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Run multi-agent DocsBot validation in AutoGen

Your AutoGen agents use `ask_bot_question` to run consensus checks on complex technical queries. One agent queries the bot, while a critic agent analyzes the response for technical accuracy. This debate loop prevents incorrect answers from reaching customers. The agents negotiate until they agree that the retrieved answer matches the source documentation.

Audit DocsBot workspaces using AutoGen agents

The `list_docsbot_teams` tool allows your AutoGen coordinator agent to map out your entire workspace structure. The coordinator then delegates specific bots to specialist agents for individual performance audits. Each specialist agent reviews its assigned bot's configuration and training status. This automated audit flags inactive bots and mismatched team configurations across your entire workspace.

Resolve source conflicts via this MCP Server

This MCP Server exposes `search_bot_sources` so your AutoGen agents can locate conflicting files within a bot's knowledge base. When two documents contain contradicting facts, the agents cross-reference the files to resolve the conflict. The agents use this tool to isolate the exact source of a support hallucination. Once identified, they flag the outdated document for human review, keeping your knowledge base clean.

Setup guide

Set up DocsBot 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 DocsBot 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="DocsBot_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent DocsBot data")
print(result.messages[-1].content)

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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="DocsBot_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent DocsBot data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DocsBot. 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 DocsBot MCP in AutoGen

One agent queries the bot using `ask_bot_question` while another audits the source files. They use `list_bot_knowledge_sources` to verify that the answer is grounded in actual training documents.

Yes, you pass the tool list from the MCP Server to specific `AssistantAgent` constructors. This allows you to restrict administrative tools like `list_docsbot_teams` to a manager agent while giving worker agents basic query tools.

Agents run `list_recently_indexed_bots` to monitor updates across your workspace. When a bot gets updated, the agent alerts the rest of the group to refresh their cached knowledge.

Yes, your analyst agent retrieves interaction history using `list_bot_interaction_logs`. The agent parses the logs to identify recurring questions that the bot failed to answer accurately.

Your workspace metadata and team bot lists pulled via `list_team_bots` are processed locally within the V8 sandbox. The MCP Server handles all authorization protocols locally, meaning no external parties can access your team configuration or API tokens.

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