How to Use the WhatsApp Chat Export Parser MCP in AutoGen

Q: How do I get a verified summary from chats using WhatsApp Chat Export Parser and AutoGen?

Run parsewhatsappchat first. Then, feed the JSON output to your AssistantAgent list. The agents will debate the best summary, forcing consensus on key takeaways and validating them against sender statistics.

Q: Can I analyze multiple chats simultaneously with AutoGen?

Yes. You can structure an initial pipeline that runs parsewhatsappchat repeatedly for different files. The resulting structured data from all sources feeds into the multi-agent conversation, allowing them to compare information across groups.

Q: Does WhatsApp Chat Export Parser help validate timelines in AutoGen?

Absolutely. The timestamp information extracted by parsewhatsappchat lets one agent verify if another agent's timeline assumption is accurate based on the raw data provided to the system.

Use multi-agent debate to analyze WhatsApp chats with the AutoGen framework and MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect WhatsApp Chat Export Parser MCP to AutoGen

Create your Vinkius account to connect WhatsApp Chat Export Parser 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.

GDPR Free for Subscribers

Setup WhatsApp Chat Export Parser with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Get consensus on chat details.

The `parse_whatsapp_chat` tool converts a messy exported file into clean JSON, giving agents reliable data. You pass this structured output to your AutoGen system. The multiple agents can then debate the findings: one might summarize key action items while another verifies that every mentioned participant actually sent a message.

Verify chat facts through agent deliberation.

Instead of relying on a single summary, you get consensus. If Agent A claims a meeting was scheduled, Agent B can challenge it by checking the timestamp data for confirmation in the JSON output. The process forces deep review of sender identities and specific message content to converge on an accurate conclusion.

Process chat history for risk flagging.

You set up specialized agents—say, a Risk Agent and a Compliance Agent. They both receive the structured JSON from `parse_whatsapp_chat`. The Risk Agent flags potentially sensitive topics while the Compliance Agent checks if any required data (like addresses) were exchanged. This multi-agent deliberation provides layered security review of your chat records.

Setup guide

Set up WhatsApp Chat Export Parser 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 WhatsApp Chat Export Parser 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="WhatsApp Chat Export Parser_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent WhatsApp Chat Export Parser 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="WhatsApp Chat Export Parser_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent WhatsApp Chat Export Parser 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 whatsapp-export. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect WhatsApp Chat Export Parser now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about WhatsApp Chat Export Parser MCP in AutoGen

Run `parse_whatsapp_chat` first. Then, feed the JSON output to your AssistantAgent list. The agents will debate the best summary, forcing consensus on key takeaways and validating them against sender statistics.

Yes. You can structure an initial pipeline that runs `parse_whatsapp_chat` repeatedly for different files. The resulting structured data from all sources feeds into the multi-agent conversation, allowing them to compare information across groups.

The server extracts messages, senders, timestamps, and participant statistics. This rich JSON data is what allows the competing perspectives of your agents to challenge each other's assumptions effectively.

Absolutely. The timestamp information extracted by `parse_whatsapp_chat` lets one agent verify if another agent's timeline assumption is accurate based on the raw data provided to the system.

This server handles highly sensitive communications, specifically messages, senders, timestamps, and participant statistics. Always manage these inputs within a secure and auditable agent environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript