How to Use the Regex Toolkit MCP in AutoGen

Let your AutoGen agents debate data integrity using Regex Toolkit tools.

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Connect Regex Toolkit MCP to AutoGen

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Setup Regex Toolkit with AutoGen

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Delegating regex tasks in AutoGen

The `extract_pattern` tool gives your agents a way to pull data objectively. If one agent finds a phone number, it can share that with the team. There is no ambiguity. The tool either returns the match or it doesn't, providing a hard fact for your agents to discuss.

Sanitizing agent communication in AutoGen

Use `mask_sensitive_data` to ensure your multi-agent conversation remains private. Agents can redact PII before passing messages to each other. It’s a protocol for safety. By forcing redaction, you ensure that no agent accidentally leaks private info in the chat history.

Agent-driven validation in AutoGen

The `validate_pattern` tool allows your agents to verify inputs from external users. An agent can challenge an input if the regex validation fails. This adds a layer of logic to your debate. Agents don't just accept input; they check it against your rules.

Setup guide

Set up Regex Toolkit 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 Regex Toolkit 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="Regex Toolkit_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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