MCP Flowise MCP Server

`mcp-flowise` is a Python package implementing a Model Context Protocol (MCP) server that integrates with the Flowise API. It provides a standardized

Local serverstdioPython

What is the MCP Flowise MCP server?

MCP Flowise MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. mcp-flowise is a Python package implementing a Model Context Protocol (MCP) server that integrates with the Flowise API. It provides a standardized and flexible way to list chatflows, create predictions, and dynamically register tools.

What you get

  • Dynamic Tool Exposure — LowLevel mode dynamically creates tools for each chatflow or assistant
  • Simpler Configuration — FastMCP mode exposes list_chatflows and create_prediction tools for minimal setup
  • Flexible Filtering — Both modes support filtering chatflows via whitelists and blacklists by IDs or names (regex)
  • MCP Integration — Integrates seamlessly into MCP workflows

What the assistant can call

Once MCP Flowise is connected, these are the calls the assistant has available:

  • FLOWISE_API_KEY — Your Flowise API Bearer token (required)
  • FLOWISE_API_ENDPOINT — Base URL for Flowise (default: http://localhost:3010)
  • FLOWISE_CHATFLOW_DESCRIPTIONS — Comma-separated list of chatflow_id:description pairs. Example:
  • FLOWISE_CHATFLOW_ID — Single Chatflow ID (optional)
  • FLOWISE_ASSISTANT_ID — Single Assistant ID (optional)
  • FLOWISE_CHATFLOW_DESCRIPTION — Optional description for the single tool exposed
  • Prerequisites — The Prerequisites tool exposed by this server
  • Notes — The Notes tool exposed by this server
  • General — The General tool exposed by this server

Configuration and credentials

You will need 8 environment variables: FLOWISE_API_KEY, FLOWISE_API_ENDPOINT, LOGLEVEL, APPDATA, FLOWISE_CHATFLOW_ID, FLOWISE_ASSISTANT_ID, FLOWISE_WHITELIST_ID, FLOWISE_BLACKLIST_ID. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Python 3.12 or higher - uvx package manager

Setting it up

Installation goes through your MCP client rather than a global install: point it at @smithery/cli on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

Choosing this one

This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MCP Flowise's toolset — FLOWISE_API_KEY, FLOWISE_API_ENDPOINT, FLOWISE_CHATFLOW_DESCRIPTIONS and 6 more — is a fair guide to whether it matches your workflow. It is maintained by andydukes; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against MCP Flowise's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 9 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch MCP Flowise.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp flowise mcp server does with a few real requests.

Available tools

ToolWhat it does
FLOWISE_API_KEYYour Flowise API Bearer token (**required**).
FLOWISE_API_ENDPOINTBase URL for Flowise (default: http://localhost:3010).
FLOWISE_CHATFLOW_DESCRIPTIONSComma-separated list of chatflow_id:description pairs. Example:
FLOWISE_CHATFLOW_IDSingle Chatflow ID (optional).
FLOWISE_ASSISTANT_IDSingle Assistant ID (optional).
FLOWISE_CHATFLOW_DESCRIPTIONOptional description for the single tool exposed.
PrerequisitesThe Prerequisites tool exposed by this server.
NotesThe Notes tool exposed by this server.
GeneralThe General tool exposed by this server.

How to install the MCP Flowise MCP server

{
  "mcpServers": {
    "flowise": {
      "command": "npx",
      "args": ["-y", "@smithery/cli"],
      "env": {
        "FLOWISE_API_KEY": "your-value",
        "FLOWISE_API_ENDPOINT": "your-value",
        "LOGLEVEL": "your-value",
        "APPDATA": "your-value",
        "FLOWISE_CHATFLOW_ID": "your-value",
        "FLOWISE_ASSISTANT_ID": "your-value",
        "FLOWISE_WHITELIST_ID": "your-value",
        "FLOWISE_BLACKLIST_ID": "your-value"
      }
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

  • Python 3.12 or higher - uvx package manager
VariableDescriptionRequired
FLOWISE_API_KEYCredential the server authenticates with.Yes
FLOWISE_API_ENDPOINTConfiguration value read at startup.Optional
LOGLEVELConfiguration value read at startup.Optional
APPDATAConfiguration value read at startup.Optional
FLOWISE_CHATFLOW_IDConfiguration value read at startup.Optional
FLOWISE_ASSISTANT_IDConfiguration value read at startup.Optional
FLOWISE_WHITELIST_IDConfiguration value read at startup.Optional
FLOWISE_BLACKLIST_IDConfiguration value read at startup.Optional

Example prompts to try

  • Use MCP Flowise to FLOWISE API KEY.
  • Use MCP Flowise to FLOWISE API ENDPOINT.
  • Use MCP Flowise to FLOWISE CHATFLOW DESCRIPTIONS.

Frequently asked questions

It connects MCP Flowise to MCP-compatible AI assistants such as Claude and Cursor, exposing 9 tools (FLOWISE_API_KEY, FLOWISE_API_ENDPOINT, FLOWISE_CHATFLOW_DESCRIPTIONS, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Flowise directly.