mcpField
C
chatflow

chatflow

Remote
chatflow.bizBusiness & Marketing0Updated 14w ago

About chatflow

ChatFlow MCP connects MCP-compatible agents to a workspace in ChatFlow, a CRM for small teams using WhatsApp, Telegram, and Instagram. Agents can search contacts, read conversations, update sales pipelines, and send messages when the workspace owner enables sending.

Key features

  1. 01Search contacts by name or phone
  2. 02Read conversations and CRM details
  3. 03View and move pipeline leads
  4. 04Update notes and deal values
  5. 05Create contacts and conversations
  6. 06Send messages with owner opt-in

Use cases

  1. 01Find a contact by name or phone number
  2. 02Review recent chats and lead details
  3. 03Move a lead to another pipeline stage
  4. 04Send a customer message when permitted

MCP support

Provides a hosted MCP server over stateless Streamable HTTP, authenticated with a bearer API key. It exposes CRM tools for contact and conversation management, pipeline updates, usage checks, and opt-in message sending.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://valuable-sockeye-14.eu-west-1.convex.site/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://valuable-sockeye-14.eu-west-1.convex.site/mcpAuth required

Tools

Details

From the project README

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.

Links

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.