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io.github.Yersat/chatflow

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WhatsApp CRM for AI agents: search contacts, read chats, manage the sales pipeline, send messages.

Source code Website Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http chatflow 'https://valuable-sockeye-14.eu-west-1.convex.site/mcp' --header 'Authorization: <Bearer <API key>. Create one in ChatFlow → Settings → AI agents (MCP).>'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "chatflow": {
            "type": "http",
            "url": "https://valuable-sockeye-14.eu-west-1.convex.site/mcp",
            "headers": {
                "Authorization": "<Bearer <API key>. Create one in ChatFlow → Settings → AI agents (MCP).>"
            }
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. ChatFlow MCP
  2. Quick start
  3. Tools
  4. Sending is opt-in
  5. Links

ChatFlow MCP

Connect your AI agent to your WhatsApp CRM.

ChatFlow is a WhatsApp/Telegram/Instagram CRM for small teams — a shared inbox, a drag-and-drop sales pipeline, AI auto-replies, and broadcast campaigns. This is its hosted MCP (Model Context Protocol) server: point Claude, Claude Code, Cursor, or any MCP-compatible agent at your workspace and it can search contacts, read conversations, manage your pipeline, and — when you allow it — send messages.

  • Endpoint: https://valuable-sockeye-14.eu-west-1.convex.site/mcp
  • Transport: Streamable HTTP (stateless)
  • Auth: Authorization: Bearer <API key> — create one in ChatFlow → Settings → AI agents (MCP)

Quick start

  1. In ChatFlow, open Settings → AI agents (MCP) (workspace owner) and click Create API key. Copy it — it's shown once. Optionally give it an expiry.
  2. Add the server to your client:

Claude Code

claude mcp add --transport http chatflow \
  https://valuable-sockeye-14.eu-west-1.convex.site/mcp \
  --header "Authorization: Bearer cfk_YOUR_KEY"

Claude.ai / Claude Desktop — Settings → Connectors → Add custom connector → paste the endpoint URL and set the Authorization: Bearer cfk_YOUR_KEY header.

Cursor — .cursor/mcp.json:

{
  "mcpServers": {
    "chatflow": {
      "url": "https://valuable-sockeye-14.eu-west-1.convex.site/mcp",
      "headers": { "Authorization": "Bearer cfk_YOUR_KEY" }
    }
  }
}

Full setup and troubleshooting: docs/setup.md.

Tools

ToolWhat it does
search_contactsFind contacts by name/phone substring
list_conversationsRecent chats with previews, unread counts, CRM fields
get_conversationOne chat: contact, notes, deal value, recent messages
list_pipelineKanban columns with the leads in each stage
move_conversationMove a lead to a pipeline column
update_leadSet notes / deal value on a conversation
create_contactCreate a WhatsApp contact + conversation from a phone number
send_messageSend a text to the customer (opt-in — see below)
get_usageSubscription tier, limits, current monthly usage

Read tools are annotated read-only; send_message is annotated as a world-affecting write so well-behaved clients confirm before calling it.

Sending is opt-in

send_message messages a real customer, so it's off by default. The workspace owner enables it with the "Allow agents to send messages" toggle in Settings. While off, agents can read everything and draft replies, but every send is rejected with a message explaining the toggle. When on, agent sends count toward your monthly quota, appear in the inbox with the AI badge, pause the auto-reply assistant on that chat (so two AIs never answer at once), and support an idempotencyKey so a retry can't double-send.

Prompt-injection note: message text and notes an agent reads are written by your customers. Keep the send toggle off unless you trust the agent driving it.

Frequently asked questions

What is io.github.Yersat/chatflow?

WhatsApp CRM for AI agents: search contacts, read chats, manage the sales pipeline, send messages.

How do I install io.github.Yersat/chatflow?

It runs as a remote server. In Claude Code: claude mcp add --transport http chatflow 'https://valuable-sockeye-14.eu-west-1.convex.site/mcp' --header 'Authorization: <Bearer <API key>. Create one in ChatFlow → Settings → AI agents (MCP).>'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.Yersat/chatflow need an API key?

Yes. It expects Authorization, which you set in its configuration.

Is io.github.Yersat/chatflow open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains io.github.Yersat/chatflow?

It is published by Yersat. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.