Question 1

What is mcp-flowise?

Accepted Answer

mcp-flowise is a Python package that implements a Model Context Protocol (MCP) server, integrating with the Flowise API. It allows for listing chatflows, creating predictions, and dynamically registering tools for Flowise chatflows or assistants.

Question 2

What is MCP?

Accepted Answer

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), enabling AI models to interact with external data sources and tools.

Question 3

What are the prerequisites for installing mcp-flowise?

Accepted Answer

To install mcp-flowise, you need Python 3.12 or higher and the `uvx` package manager.

Question 4

How do I install mcp-flowise?

Accepted Answer

You can install mcp-flowise via Smithery or by using `uvx` directly from the GitHub repository. Detailed installation steps are provided in the documentation.

Question 5

What are the modes of operation in mcp-flowise?

Accepted Answer

mcp-flowise supports two modes: FastMCP (Simple) mode and LowLevel mode. FastMCP mode exposes `list_chatflows` and `create_prediction` tools, while LowLevel mode dynamically registers all chatflows as separate tools.

Question 6

How do I enable FastMCP mode?

Accepted Answer

Enable FastMCP mode by setting the environment variable `FLOWISE_SIMPLE_MODE` to `true`.

Question 7

What environment variables are required for mcp-flowise?

Accepted Answer

The required environment variables include `FLOWISE_API_KEY` (your Flowise API Bearer token) and `FLOWISE_API_ENDPOINT` (Base URL for Flowise).

Question 8

How can I filter chatflows in mcp-flowise?

Accepted Answer

Filters can be applied using environment variables such as `FLOWISE_WHITELIST_ID`, `FLOWISE_BLACKLIST_ID`, `FLOWISE_WHITELIST_NAME_REGEX`, and `FLOWISE_BLACKLIST_NAME_REGEX`.

Question 9

How do I protect my Flowise API key?

Accepted Answer

Ensure the `FLOWISE_API_KEY` is kept secure and not exposed in logs or repositories. Use `.env` files or environment variables for sensitive configurations and add `.env` to your `.gitignore` file.

Question 10

What should I do if I encounter connection errors?

Accepted Answer

Verify that the `FLOWISE_API_ENDPOINT` is reachable and that your Flowise server is running.

Question 11

Can I run mcp-flowise on Windows?

Accepted Answer

Yes, but running `mcp-flowise` on Windows with `uvx` requires a specific configuration, including using full paths to `uvx.exe` and the cloned repository.

Question 12

What is UBOS?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. Our platform helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model, and create Multi-Agent Systems.

Question 13

How does mcp-flowise integrate with UBOS?

Accepted Answer

mcp-flowise allows UBOS users to leverage their Flowise chatflows within the UBOS platform, enabling the creation of intelligent AI agents that automate tasks, improve customer support, and drive business growth.

Question 14

What are some use cases for mcp-flowise with UBOS?

Accepted Answer

Use cases include enhanced customer support AI agents, streamlined sales and marketing automation, improved internal knowledge management, and advanced data analysis and reporting.

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