mcp-flowise

MCP server that exposes the chatflows of your local Flowise as tools for Claude, Cursor, free-code, or any MCP client.

Tools

Simple mode (default):

• list_chatflows() — lists available chatflows (id + name).
• create_prediction(chatflow_id, question) — runs a chatflow and returns its response.

Dynamic mode (FLOWISE_DYNAMIC=true):

• Registers one tool per chatflow at startup, e.g. flowise_support_bot(question).

Requirements

• A running Flowise instance (default http://localhost:3000)
• Node.js 18+ or Python 3.10+ with uv

---

Installation

One-command install (any client)

npx -y @suamkf08/mcp-flowise-install --client claude
npx -y @suamkf08/mcp-flowise-install --client cursor
npx -y @suamkf08/mcp-flowise-install --client free-code
npx -y @suamkf08/mcp-flowise-install --client vscode
npx -y @suamkf08/mcp-flowise-install --client windsurf

The script asks for your FLOWISE_API_ENDPOINT and FLOWISE_API_KEY, writes the config automatically, and tells you where it was saved. Restart your client after running it.

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Manual install

Claude Desktop

Add this to your claude_desktop_config.json (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):

Option A — via npm (Node.js required):

{
  "mcpServers": {
    "mcp-flowise": {
      "command": "npx",
      "args": ["-y", "@suamkf08/mcp-flowise"],
      "env": {
        "FLOWISE_API_ENDPOINT": "http://localhost:3000",
        "FLOWISE_API_KEY": ""
      }
    }
  }
}

Option B — via uvx (uv required):

Install uv first if you don't have it:

# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Then add to claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-flowise": {
      "command": "uvx",
      "args": ["mcp-flowise"],
      "env": {
        "FLOWISE_API_ENDPOINT": "http://localhost:3000",
        "FLOWISE_API_KEY": ""
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project (or ~/.cursor/mcp.json globally):

{
  "mcpServers": {
    "mcp-flowise": {
      "command": "npx",
      "args": ["-y", "@suamkf08/mcp-flowise"],
      "env": {
        "FLOWISE_API_ENDPOINT": "http://localhost:3000",
        "FLOWISE_API_KEY": ""
      }
    }
  }
}

free-code

Add to ~/.free-code/agent/mcp.json (or import with /mcp-import):

{
  "mcpServers": {
    "mcp-flowise": {
      "command": "npx",
      "args": ["-y", "@suamkf08/mcp-flowise"],
      "env": {
        "FLOWISE_API_ENDPOINT": "http://localhost:3000",
        "FLOWISE_API_KEY": ""
      }
    }
  }
}

Then enable it in free-code:

/mcp enable mcp-flowise
/reload

---

Configuration

Environment variable	Default	Description
FLOWISE_API_ENDPOINT	http://localhost:3000	Base URL of your Flowise instance
FLOWISE_API_KEY	(empty)	Bearer token (Flowise → Settings → API Keys)
FLOWISE_DYNAMIC	false	Set to true to register one tool per chatflow
FLOWISE_WHITELIST_ID	(empty)	Comma-separated chatflow IDs to include
FLOWISE_BLACKLIST_ID	(empty)	Comma-separated chatflow IDs to exclude
FLOWISE_WHITELIST_NAME_REGEX	(empty)	Only include chatflows whose name matches
FLOWISE_BLACKLIST_NAME_REGEX	(empty)	Exclude chatflows whose name matches

---

Development

git clone https://github.com/suamkf08/mcp-flowise
cd mcp-flowise
uv run mcp-flowise        # starts over stdio; Ctrl+C to quit

Inspect with MCP Inspector:

uv run mcp dev mcp_flowise/server.py

Flowise API reference

• List chatflows: GET {endpoint}/api/v1/chatflows
• Run chatflow: POST {endpoint}/api/v1/prediction/{chatflowId} with {"question": "..."}
• Auth header: Authorization: Bearer <FLOWISE_API_KEY>