How do I find my API Key in Flowise?

Log in to your Flowise dashboard and click on the **API Keys** tab in the sidebar to generate or copy your unique token.

Does this support multi-tenant instances?

Yes! Ensure you provide the full Instance URL and the API Key corresponding to the specific environment you want to manage.

Can I push documents to vector stores via AI?

Absolutely. Use the `upsert_vector_data` tool by providing the `chatflow_id` and the JSON payload containing your document data.

INSTANT PLUG AND PLAY

FlowiseAI MCP Server for WindsurfGive Windsurf instant access to 12 tools to Execute Chatflow Prediction, Get Chatflow Details, Get Server Version, and more

Name: FlowiseAI
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools IDE

Windsurf brings agentic AI coding to a purpose-built IDE. Connect FlowiseAI through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.

Use with Your AI Agent

Ask AI about this App Connector for Windsurf

Open in ChatGPT Open in Claude Open in Perplexity

The FlowiseAI app connector for Windsurf is a standout in the Friends Mcp category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

RecommendedModern Approach — Zero Configuration

Vinkius Desktop App

The modern way to manage MCP Servers — no config files, no terminal commands. Install FlowiseAI and 3,400+ MCP Servers from a single visual interface.

Download Free Open SourceNo signup required

Classic Setup·json

{
  "mcpServers": {
    "flowiseai": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About FlowiseAI MCP Server

Connect your FlowiseAI (self-hosted) instance to any AI agent and take full control of your LLM orchestration and RAG workflows through natural conversation.

Windsurf's Cascade agent chains multiple FlowiseAI tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 12 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.

What you can do

Prediction Orchestration — Trigger specific chatflows and retrieve LLM-generated responses programmatically using natural language inputs
Chatflow Management — List all orchestration flows and retrieve detailed technical structures and metadata to monitor your AI agents
Vector Intelligence — Programmatically upsert documents or raw data into the vector stores linked to your chatflows to ensure high-fidelity context
Component Oversight — Access server-wide credentials, custom tools, and global variables to manage your complete Flowise ecosystem
Operational Visibility — Monitor user feedback, leads, and assistant profiles directly through your agent for instant reporting

The FlowiseAI MCP Server exposes 12 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 FlowiseAI tools available for Windsurf

When Windsurf connects to FlowiseAI through Vinkius, your AI agent gets direct access to every tool listed below — spanning llm-workflows, rag-pipelines, chatbot-development, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

execute_chatflow_prediction

Trigger an LLM flow prediction

get_chatflow_details

Get details for a specific chatflow

get_server_version

Get Flowise server version

list_ai_assistants

List OpenAI-style assistants

list_chat_feedback

List user feedback for a chatflow

list_chatflows

List all LLM orchestration flows

list_external_tools

List custom tools

list_flow_leads

List captured leads

list_flow_variables

List global variables

list_flowise_credentials

List configured credentials

list_marketplace_templates

List chatflow templates

upsert_vector_data

Push data into a vector store

Connect FlowiseAI to Windsurf via MCP

Follow these steps to wire FlowiseAI into Windsurf. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"

Add the server

Paste the JSON configuration above into mcp_config.json

Save and reload

Windsurf will detect the new server automatically

Start using FlowiseAI

Open Cascade and ask: "Using FlowiseAI, help me...". 12 tools available

Why Use Windsurf with the FlowiseAI MCP Server

Windsurf provides unique advantages when paired with FlowiseAI through the Model Context Protocol.

Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention

Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively

JSON-based configuration means zero code changes: paste a URL, reload, and all 12 tools are immediately available

Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts

FlowiseAI + Windsurf Use Cases

Practical scenarios where Windsurf combined with the FlowiseAI MCP Server delivers measurable value.

Automated code generation: ask Cascade to fetch data from FlowiseAI and generate models, types, or handlers based on real API responses

Live debugging: query FlowiseAI tools mid-session to inspect production data while debugging without leaving the editor

Documentation generation: pull schema information from FlowiseAI and have Cascade generate comprehensive API docs automatically

Rapid prototyping: combine FlowiseAI data with Cascade's code generation to scaffold entire features in minutes

Example Prompts for FlowiseAI in Windsurf

Ready-to-use prompts you can give your Windsurf agent to start working with FlowiseAI immediately.

"List all my chatflows in Flowise."

"Execute chatflow 'cf_1' with question: 'How do I reset my password?'"

"Upsert this data into vector store for chatflow 'cf_2': [data]"

Troubleshooting FlowiseAI MCP Server with Windsurf

Common issues when connecting FlowiseAI to Windsurf through the Vinkius, and how to resolve them.

Server not connecting

Check Settings → MCP for the server status. Try toggling it off and on.

FlowiseAI + Windsurf FAQ

Common questions about integrating FlowiseAI MCP Server with Windsurf.

How does Windsurf discover MCP tools?

Windsurf reads the mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.

Can Cascade chain multiple MCP tool calls?

Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.

Does Windsurf support multiple MCP servers?

Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.