Flowise
About
Integrates with Flowise API to enable interaction with chatflows and assistants through dynamic tool registration or simplified static tools for listing and prediction creation.
Details
- Author
- andydukes
- Repository
- andydukes/mcp-flowise
- License
- MIT License
- Categories
- Developer Tools, AI, API, Automation, Productivity, Community, Communication
- Tags
- #integration
Jump to
- 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.
---
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
FlowiseCommand (node, npx, python, etc.)uvxArguments-
Argument 1
--from -
Argument 2
git+https://github.com/andydukes/mcp-flowise -
Argument 3
mcp-flowise
Environment-
FLOWISE_API_KEY
$${FLOWISE_API_KEY} -
FLOWISE_API_ENDPOINT
$${FLOWISE_API_ENDPOINT}
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
To install mcp-flowise for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @andydukes/mcp-flowise --client claude
Confirm you can run the server directly from the GitHub repository using uvx:
uvx --from git+https://github.com/andydukes/mcp-flowise mcp-flowise
You can integrate mcp-flowise into your MCP ecosystem by adding it to the mcpServers configuration. Example:
{
"mcpServers": {
"mcp-flowise": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/andydukes/mcp-flowise",
"mcp-flowise"
],
"env": {
"FLOWISE_API_KEY": "${FLOWISE_API_KEY}",
"FLOWISE_API_ENDPOINT": "${FLOWISE_API_ENDPOINT}"
}
}
}
}
---
If you're using uvx on Windows and encounter issues with --from git+https, the recommended solution is to clone the repository locally and configure the mcpServers with the full path to uvx.exe and the cloned repository. Additionally, include APPDATA, LOGLEVEL, and other environment variables as required.
{
"mcpServers": {
"flowise": {
"command": "C:\\Users\\matth\\.local\\bin\\uvx.exe",
"args": [
"--from",
"C:\\Users\\matth\\downloads\\mcp-flowise",
"mcp-flowise"
],
"env": {
"LOGLEVEL": "ERROR",
"APPDATA": "C:\\Users\\matth\\AppData\\Roaming",
"FLOWISE_API_KEY": "your-api-key-goes-here",
"FLOWISE_API_ENDPOINT": "http://localhost:3010/"
}
}
}
}
list_chatflows
Lists all available chatflows. No parameters required.
create_prediction
Creates a prediction based on a specified chatflow. Parameters may include chatflow ID and input data.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"flowise": {
"env": {
"FLOWISE_API_KEY": "$${FLOWISE_API_KEY}",
"FLOWISE_API_ENDPOINT": "$${FLOWISE_API_ENDPOINT}"
},
"args": [
"--from",
"git+https://github.com/andydukes/mcp-flowise",
"mcp-flowise"
],
"command": "uvx"
}
}
}
Linux
{
"env": {
"FLOWISE_API_KEY": "$${FLOWISE_API_KEY}",
"FLOWISE_API_ENDPOINT": "$${FLOWISE_API_ENDPOINT}"
},
"args": [
"--from",
"git+https://github.com/andydukes/mcp-flowise",
"mcp-flowise"
],
"command": "uvx"
}
Macos
{
"env": {
"FLOWISE_API_KEY": "$${FLOWISE_API_KEY}",
"FLOWISE_API_ENDPOINT": "$${FLOWISE_API_ENDPOINT}"
},
"args": [
"--from",
"git+https://github.com/andydukes/mcp-flowise",
"mcp-flowise"
],
"command": "uvx"
}
Windows
{
"env": {
"APPDATA": "C:\\Users\\matth\\AppData\\Roaming",
"LOGLEVEL": "ERROR",
"FLOWISE_API_KEY": "your-api-key-goes-here",
"FLOWISE_API_ENDPOINT": "http://localhost:3010/"
},
"args": [
"--from",
"C:\\Users\\matth\\downloads\\mcp-flowise",
"mcp-flowise"
],
"command": "C:\\Users\\matth\\.local\\bin\\uvx.exe"
}
mcp-flowise
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 for Flowise chatflows or assistants.
It supports two operation modes:
- LowLevel Mode (Default): Dynamically registers tools for all chatflows retrieved from the Flowise API.
- FastMCP Mode: Provides static tools for listing chatflows and creating predictions, suitable for simpler configurations.
<p align="center">
</p>
---
Features
- 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.
---
Installation
Installing via Smithery
To install mcp-flowise for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @andydukes/mcp-flowise --client claude
Prerequisites
- Python 3.12 or higher
- uvx package manager
Install and Run via uvx
Confirm you can run the server directly from the GitHub repository using uvx:
uvx --from git+https://github.com/andydukes/mcp-flowise mcp-flowise
Adding to MCP Ecosystem (mcpServers Configuration)
You can integrate mcp-flowise into your MCP ecosystem by adding it to the mcpServers configuration. Example:
{
"mcpServers": {
"mcp-flowise": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/andydukes/mcp-flowise",
"mcp-flowise"
],
"env": {
"FLOWISE_API_KEY": "${FLOWISE_API_KEY}",
"FLOWISE_API_ENDPOINT": "${FLOWISE_API_ENDPOINT}"
}
}
}
}
---
Modes of Operation
1. FastMCP Mode (Simple Mode)
Enabled by setting FLOWISE_SIMPLE_MODE=true. This mode:
- Exposes two tools: list_chatflows and create_prediction.
- Allows static configuration using FLOWISE_CHATFLOW_ID or FLOWISE_ASSISTANT_ID.
- Lists all available chatflows via list_chatflows.
<p align="center">
</p>
2. LowLevel Mode (FLOWISE_SIMPLE_MODE=False)
Features:
- Dynamically registers all chatflows as separate tools.
- Tools are named after chatflow names (normalized).
- Uses descriptions from the FLOWISE_CHATFLOW_DESCRIPTIONS variable, falling back to chatflow names if no description is provided.
Example:
- my_tool(question: str) -> str dynamically created for a chatflow.
---
Running on Windows with uvx
If you're using uvx on Windows and encounter issues with --from git+https, the recommended solution is to clone the repository locally and configure the mcpServers with the full path to uvx.exe and the cloned repository. Additionally, include APPDATA, LOGLEVEL, and other environment variables as required.
Example Configuration for MCP Ecosystem (mcpServers on Windows)
{
"mcpServers": {
"flowise": {
"command": "C:\\Users\\matth\\.local\\bin\\uvx.exe",
"args": [
"--from",
"C:\\Users\\matth\\downloads\\mcp-flowise",
"mcp-flowise"
],
"env": {
"LOGLEVEL": "ERROR",
"APPDATA": "C:\\Users\\matth\\AppData\\Roaming",
"FLOWISE_API_KEY": "your-api-key-goes-here",
"FLOWISE_API_ENDPOINT": "http://localhost:3010/"
}
}
}
}
Notes
- Full Paths: Use full paths for both uvx.exe and the cloned repository.
- Environment Variables: Point APPDATA to your Windows user profile (e.g., C:\\Users\\<username>\\AppData\\Roaming) if needed.
- Log Level: Adjust LOGLEVEL as needed (ERROR, INFO, DEBUG, etc.).
Environment Variables
General
- FLOWISE_API_KEY: Your Flowise API Bearer token (required).
- FLOWISE_API_ENDPOINT: Base URL for Flowise (default: http://localhost:3010).
LowLevel Mode (Default)
- FLOWISE_CHATFLOW_DESCRIPTIONS: Comma-separated list of chatflow_id:description pairs. Example:
FLOWISE_CHATFLOW_DESCRIPTIONS="abc123:Chatflow One,xyz789:Chatflow Two"
FastMCP Mode (FLOWISE_SIMPLE_MODE=true)
- FLOWISE_CHATFLOW_ID: Single Chatflow ID (optional).
- FLOWISE_ASSISTANT_ID: Single Assistant ID (optional).
- FLOWISE_CHATFLOW_DESCRIPTION: Optional description for the single tool exposed.
---
Filtering Chatflows
Filters can be applied in both modes using the following environment variables:
- Whitelist by ID:
FLOWISE_WHITELIST_ID="id1,id2,id3"
- Blacklist by ID:
FLOWISE_BLACKLIST_ID="id4,id5"
- Whitelist by Name (Regex):
FLOWISE_WHITELIST_NAME_REGEX=".important."
- Blacklist by Name (Regex):
FLOWISE_BLACKLIST_NAME_REGEX=".deprecated."
> Note: Whitelists take precedence over blacklists. If both are set, the most restrictive rule is applied.
-
Security
- Protect Your API Key: Ensure the FLOWISE_API_KEY is kept secure and not exposed in logs or repositories.
- Environment Configuration: Use .env files or environment variables for sensitive configurations.
Add .env to your .gitignore:
```bash
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