Integrate FlowiseAI with Claude, Cursor, Chatbots & AI Agents MCP Server

Q: Can I push documents to vector stores via AI?

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

Build LLM orchestration flows visually with a drag-and-drop interface for creating AI chatbots, agents, and RAG pipelines.

GDPR Free for Subscribers

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

execute

Execute chatflow prediction on FlowiseAI

Trigger an LLM flow prediction

get

Get chatflow details on FlowiseAI

Get details for a specific chatflow

get

Get server version on FlowiseAI

Get Flowise server version

list

List ai assistants on FlowiseAI

List OpenAI-style assistants

list

List chat feedback on FlowiseAI

List user feedback for a chatflow

list

List chatflows on FlowiseAI

List all LLM orchestration flows

list

List external tools on FlowiseAI

List custom tools

list

List flow leads on FlowiseAI

List captured leads

list

List flow variables on FlowiseAI

List global variables

list

List flowise credentials on FlowiseAI

List configured credentials

list

List marketplace templates on FlowiseAI

List chatflow templates

upsert

Upsert vector data on FlowiseAI

Push data into a vector store

Security & Code Integrity Audit

Every tool in the FlowiseAI MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.

A+Score: 100

How Vinkius protects your data

Can I audit what my AI agents are doing with this integration?

Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.

What happens if the underlying API rate limits my agent?

Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.

What if the AI ends up reading customer data or confidential information?

We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.

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.

FlowiseAI Capabilities for AI Assistants

Add the FlowiseAI tool to your AI Agents. The toolkit allows Claude and ChatGPT to securely fetch and update targeted data.

Execute llm workflows Commands with AI

Build automated workflows involving llm workflows by connecting FlowiseAI. It provides Claude and ChatGPT with direct API hooks into your friends mcp ecosystem.

Scaling rag pipelines via MCP

Integrate FlowiseAI for AI-driven rag pipelines management. The MCP server structures the outputs required for Claude to analyze friends mcp data.