# Flowise

> Use this tool when you need to integrate AI-powered conversational interfaces into your existing systems, or require a standardized interface for interacting with chatflows and assistants. Flowise provides a seamless connection to the Model Context Protocol (MCP), allowing for flexible configuration and dynamic selection of chatflows and assistants. It solves the problem of incorporating AI capabilities into MCP-based applications, enabling easy integration and streamlined conversational interfaces.

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

## Description

This Flowise integration, developed by Matthew Hand, provides a seamless connection between Flowise and the Model Context Protocol (MCP). It allows users to interact with Flowise chatflows and assistants through a standardized MCP interface, enabling easy integration into existing MCP-compatible systems. The implementation offers flexibility in configuration, supporting both specific chatflow/assistant locking and dynamic selection. It's particularly useful for developers looking to incorporate Flowise's AI capabilities into their MCP-based applications, streamlining the process of AI-powered conversational interfaces and predictions.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/matthewhand-flowise)
- **Repository:** <https://github.com/matthewhand/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": "matthewhand-flowise"
    }
  }
}
```

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