How to Use the WhatsApp Chat Export Parser MCP in Claude Code

Q: What format does WhatsApp Chat Export Parser require?

It requires a standard text file export (.txt) generated from WhatsApp's 'Chat > Export Chat' feature. The tool handles the parsing of that specific messy structure.

Q: How do I connect WhatsApp Chat Export Parser using Claude Code?

You run a simple command: claude mcp add --transport http .... Once connected, you verify it with claude mcp list and use the tool in your shell scripts.

Run chat data processing in CI/CD with the WhatsApp Chat Export Parser via Claude Code.

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Connect WhatsApp Chat Export Parser MCP to Claude Code

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Setup WhatsApp Chat Export Parser with Claude Code

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Scriptable Data Parsing

The `parse_whatsapp_chat` tool executes headlessly. You can pipe a WhatsApp chat export `.txt` file into a script, and the output is immediately structured JSON. This makes it a reliable step in any CI/CD pipeline that needs to ingest communication data.

Automated Metadata Extraction

Claude Code uses this tool to extract messages, senders, and timestamps for batch processing. You don't need a GUI; you just need a consistent stream of input files. This capability lets you run data cleanup jobs on chat message exports automatically.

Pipeline Reporting

You can design a job that first runs `parse_whatsapp_chat` and then uses the resulting JSON to calculate participant statistics. This sequence of operations is perfect for nightly cron jobs or GitHub Actions. It’s purely functional: input file in, structured report out.

Setup guide

Set up WhatsApp Chat Export Parser MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see whatsapp-chat-export-parser-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest WhatsApp Chat Export Parser transactions." It will automatically discover and invoke the available WhatsApp Chat Export Parser tools.

Terminal

claude mcp add --transport http whatsapp-chat-export-parser-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the WhatsApp Chat Export Parser MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "whatsapp-chat-export-parser-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about WhatsApp Chat Export Parser MCP in Claude Code

Yep. Because it's designed for headless execution and supports standard transports, you can easily schedule the parsing of chat exports using cron jobs or GitHub Actions.

It requires a standard text file export (`.txt`) generated from WhatsApp's 'Chat > Export Chat' feature. The tool handles the parsing of that specific messy structure.

You run a simple command: `claude mcp add --transport http ...`. Once connected, you verify it with `claude mcp list` and use the tool in your shell scripts.

Since Claude Code executes in a terminal or Docker container, the processing of chat messages happens entirely within that environment. It's ideal for sensitive message analysis where you don't want cloud exposure.

It processes raw text messages and associated metadata—like timestamps, sender IDs, and participant counts—converting them into JSON for downstream consumption by other tools.

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