Flowise
Integrate with the Flowise API to create predictions and manage chatflows and assistants.
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.
Features
- Dynamic Tool Exposure: LowLevel mode dynamically creates tools for each chatflow or assistant.
- Simpler Configuration: FastMCP mode exposes
list_chatflowsandcreate_predictiontools 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
uvxpackage 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_chatflowsandcreate_prediction. - Allows static configuration using
FLOWISE_CHATFLOW_IDorFLOWISE_ASSISTANT_ID. - Lists all available chatflows via
list_chatflows.
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_DESCRIPTIONSvariable, falling back to chatflow names if no description is provided.
Example:
my_tool(question: str) -> strdynamically 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.exeand the cloned repository. - Environment Variables: Point
APPDATAto your Windows user profile (e.g.,C:\\Users\\<username>\\AppData\\Roaming) if needed. - Log Level: Adjust
LOGLEVELas 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 ofchatflow_id:descriptionpairs. 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_KEYis kept secure and not exposed in logs or repositories. - Environment Configuration: Use
.envfiles or environment variables for sensitive configurations.
Add .env to your .gitignore:
# .gitignore
.env
Troubleshooting
- Missing API Key: Ensure
FLOWISE_API_KEYis set correctly. - Invalid Configuration: If both
FLOWISE_CHATFLOW_IDandFLOWISE_ASSISTANT_IDare set, the server will refuse to start. - Connection Errors: Verify
FLOWISE_API_ENDPOINTis reachable.
License
This project is licensed under the MIT License. See the LICENSE file for details.
TODO
- Fastmcp mode
- Lowlevel mode
- Filtering
- Claude desktop integration
- Assistants
Serveurs connexes
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
MCP Base Server
A base template for creating new MCP servers, designed for easy containerized deployment with Docker.
Multiverse MCP Server
A middleware server for running multiple, isolated instances of MCP servers with unique namespaces and configurations.
SheetsData
Instant access to electronic component datasheets for AI agents — specs, pinouts, package info, and absolute max ratings extracted from manufacturer PDFs on demand.
WireMCP
Empowers LLMs with real-time network traffic analysis using tshark. Requires Wireshark's tshark to be installed.
OpsLevel
Interact with your OpsLevel account using read-only access.
MCP Command Server
A server for securely executing commands on the host system, requiring Java 21 or higher.
MCP Tool Kit
A modular server for building AI agents with a unified interface for tools like file operations, web search, browser automation, and financial data.
Merge MCP Server
Integrates the Merge Unified API with any LLM provider using the MCP protocol.
Tempo MCP Server
An MCP server for querying distributed tracing data from Grafana Tempo.
Puppeteer MCP
MCP server for browser automation via Puppeteer