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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.

Code source Site web Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

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).>'
Configuration JSON (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

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  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.

Questions fréquentes

Qu'est-ce que io.github.Yersat/chatflow ?

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

Comment installer io.github.Yersat/chatflow ?

Il fonctionne comme serveur distant. Dans 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).>'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour io.github.Yersat/chatflow ?

Oui. Il attend Authorization, à renseigner dans sa configuration.

io.github.Yersat/chatflow est-il open source ?

Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.

Qui maintient io.github.Yersat/chatflow ?

Il est publié par Yersat. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.