How to Use the Document Paginator Engine MCP in AutoGen

Let your AutoGen agents debate and process complex legal text using token-safe chunks.

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Connect Document Paginator Engine MCP to AutoGen

Create your Vinkius account to connect Document Paginator Engine 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 Document Paginator Engine with AutoGen

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Run `chunk_legal_document` inside AutoGen debates

The `chunk_legal_document` tool gives your AutoGen agents the ability to slice massive contracts into manageable blocks during their discussions. A review agent can request specific chunks to analyze before debating with a compliance agent. Because the tool guarantees that sentences are never truncated, your agents don't argue over incomplete legal clauses. They negotiate using the exact, unbroken context of the contract.

Power multi-agent consensus with this MCP Server

The `chunk_legal_document` tool on this MCP Server acts as the data foundation for your AutoGen multi-agent workflows. When a performance agent demands smaller inputs, the tool calculates the exact token budget needed to satisfy the group. The agents can cooperatively process large legal files, passing clean chunks back and forth until they reach a consensus. This prevents token overflow errors from stalling your agent conversations.

Automate legal document analysis in AutoGen

Using the `chunk_legal_document` tool allows your AutoGen agents to coordinate complex document parsing tasks autonomously. One agent slices the document, while another validates the legal citations preserved in each chunk. This division of labor keeps your token usage low and your processing pipeline running smoothly. Your agents handle the heavy lifting without manual intervention.

Setup guide

Set up Document Paginator Engine 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 Document Paginator Engine 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="Document Paginator Engine_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Document Paginator Engine 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="Document Paginator Engine_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

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Common questions about Document Paginator Engine MCP in AutoGen

One agent calls the chunking tool to break down a file, then distributes the clean, token-safe chunks to other agents in the conversation for parallel analysis.

Yes. You use the AutoGen MCP adapter to convert the server tools and pass them directly into the AssistantAgent constructor.

Yes. The server connects via standard streamable HTTP parameters, allowing your AutoGen agents to fetch chunks during live conversations.

The tool automatically detects legal citations and prevents them from being split, so your debating agents always reference valid legal sources.

The server runs in a secure V8 isolate sandbox with token-based authentication. Your legal text chunks are processed entirely in-memory inside the MCP environment and destroyed immediately after execution.

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