# Flowise

> Use this tool when you need to integrate Flowise chatflows and assistants with AI conversations, enabling seamless interaction and leveraging existing workflows. It solves problems of fragmented workflows and limited AI assistant capabilities, providing a bridge between Claude Desktop and Flowise API. With inputs of chatflow data and outputs of dynamic tool registrations or static tools, use Flowise in contexts where you want to enhance AI assistant conversations with Flowise workflows.

Canonical page: https://skillsregistry.net/skills/andydukes-flowise  
JSON: https://api.skillsregistry.net/v1/skills/andydukes-flowise

## Description

MCP-Flowise provides a bridge between Claude Desktop and Flowise API, enabling AI assistants to interact with Flowise chatflows and assistants. Developed by Matthew Hand, it offers two operation modes: LowLevel Mode dynamically registers tools for each chatflow retrieved from the Flowise API, while FastMCP Mode provides simpler static tools for listing chatflows and creating predictions. The implementation supports filtering chatflows via whitelists and blacklists, integrates seamlessly with Claude Desktop through Smithery, and is particularly valuable for users who want to leverage their existing Flowise workflows directly within AI assistant conversations.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/andydukes-flowise)
- **Repository:** <https://github.com/andydukes/mcp-flowise>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "andydukes-flowise"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/andydukes-flowise` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/andydukes-flowise/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt