How to Use the Flowise MCP in Pydantic AI

Q: Can I use Flowise credentials in Pydantic AI agents?

You check your available credentials via listcredentials. This allows your agent to confirm it has the necessary access before attempting a run.

Q: Is it easy to switch flows in Pydantic AI?

Yes, listchatflows updates your agent's available tools dynamically. You just call the new flow ID in your next predict request.

Build type-safe agents with Pydantic AI and Flowise by validating every prediction result against your own data models.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Flowise MCP to Pydantic AI

Create your Vinkius account to connect Flowise to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Flowise with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe predictions for Pydantic AI

Execute `predict` and map the output to your Pydantic models. If the server returns bad data, your agent catches the validation error immediately. This stops silent corruption. Your agent only proceeds if the response matches the structure you defined in your code.

Audit execution logs with Pydantic AI

Call `get_history` to pull raw execution logs into your agent. You can then parse these logs into a structured object for analysis or reporting. It gives you full insight into the flow's behavior. You see the exact input and output pairs from past runs.

List and manage flows in Pydantic AI

Use `list_agentflows` to populate your agent's tool registry. This ensures that every workflow is correctly typed and ready for use in your pipeline. It keeps your agent's toolset dynamic. You add or remove flows without rewriting your core logic.

Setup guide

Set up Flowise MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "flowise-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Flowise tools.",
)

result = await agent.run("List recent Flowise transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flowise. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Flowise now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Flowise MCP in Pydantic AI

Yes, because you can define your models to match the tool responses. `predict` outcomes are validated at runtime, ensuring complete data integrity.

When a tool call fails, the validation layer catches it. You handle the error in your agent's response logic, keeping your system stable.

You check your available credentials via `list_credentials`. This allows your agent to confirm it has the necessary access before attempting a run.

We use a zero-trust architecture. All inputs and outputs are contained within a temporary sandbox, and no persistent storage is used for your sensitive requests.

Yes, `list_chatflows` updates your agent's available tools dynamically. You just call the new flow ID in your next `predict` request.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python