Activepieces MCP Server for Pydantic AIGive Pydantic AI instant access to 32 tools to Add Piece, Apply Flow Operation, Configure Git Repo, and more

Name: Activepieces
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Activepieces through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Activepieces MCP Server for Pydantic AI is a standout in the Productivity category — giving your AI agent 32 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Activepieces "
            "(32 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Activepieces?"
    )
    print(result.data)

asyncio.run(main())

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 Activepieces MCP Server

Connect your Activepieces account to any AI agent to orchestrate complex automations and monitor your business workflows through natural language.

Pydantic AI validates every Activepieces tool response against typed schemas, catching data inconsistencies at build time. Connect 32 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Flow Management — List, create, retrieve, and delete automation flows within your projects using list_flows and create_flow.
Execution Monitoring — Track flow runs, check statuses, and inspect detailed step results for debugging with list_flow_runs and get_flow_run.
App Connections — Manage credentials and connections for external services like Slack, Discord, or Google Sheets via list_app_connections.
Flow Operations — Apply structural changes or status updates to existing flows programmatically using apply_flow_operation.
Organization — List and manage folders to keep your automation workspace tidy with list_folders.

The Activepieces MCP Server exposes 32 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 32 Activepieces tools available for Pydantic AI

When Pydantic AI connects to Activepieces through Vinkius, your AI agent gets direct access to every tool listed below — spanning workflow-automation, no-code, business-process, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add piece on Activepieces

Add a custom piece to the platform

apply

Apply flow operation on Activepieces

g., MOVE_ACTION, CHANGE_STATUS). Apply an operation to a flow

configure

Configure git repo on Activepieces

Configure Git sync for a project

create

Create flow on Activepieces

Create a new flow

create

Create folder on Activepieces

Create a new folder

create

Create project on Activepieces

Create a new project

create

Create project release on Activepieces

Create a project release

delete

Delete app connection on Activepieces

Delete an app connection

delete

Delete flow on Activepieces

Delete a flow by ID

delete

Delete folder on Activepieces

Delete a folder

delete

Delete global connection on Activepieces

Delete a global connection

delete

Delete project member on Activepieces

Remove a member from a project

get

Get flow on Activepieces

Get a specific flow by ID

get

Get flow run on Activepieces

Get detailed execution data for a flow run

get

Get mcp server on Activepieces

Get MCP server configuration for AI assistants

invite

Invite user on Activepieces

Invite a user to the platform or project

list

List app connections on Activepieces

List app connections

list

List flow runs on Activepieces

List flow runs

list

List flows on Activepieces

List automation flows

list

List folders on Activepieces

List folders

list

List global connections on Activepieces

List global connections

list

List project members on Activepieces

List members of a project

list

List projects on Activepieces

List projects

list

List records on Activepieces

List records in a table

list

List tables on Activepieces

List internal data tables

list

List users on Activepieces

List users

rotate

Rotate mcp token on Activepieces

Rotate MCP token for a project

update

Update folder on Activepieces

Update a folder name

update

Update project on Activepieces

Update project settings

update

Update record on Activepieces

Update a specific record

upsert

Upsert app connection on Activepieces

Supports SECRET_TEXT, OAUTH2, BASIC_AUTH, CUSTOM_AUTH, etc. Create or update an app connection

upsert

Upsert global connection on Activepieces

Create or update a global connection

Connect Activepieces to Pydantic AI via MCP

Follow these steps to wire Activepieces into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 32 tools from Activepieces with type-safe schemas

Why Use Pydantic AI with the Activepieces MCP Server

Pydantic AI provides unique advantages when paired with Activepieces through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Activepieces integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Activepieces connection logic from agent behavior for testable, maintainable code

Activepieces + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Activepieces MCP Server delivers measurable value.

Type-safe data pipelines: query Activepieces with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Activepieces tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Activepieces and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Activepieces responses and write comprehensive agent tests

Example Prompts for Activepieces in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Activepieces immediately.

"List all active automation flows in project 'proj_123'."

"Show me the last 5 runs for flow ID 'flow_1'."

"Create a new flow named 'Customer Support Sync' in project 'proj_123'."

Troubleshooting Activepieces MCP Server with Pydantic AI

Common issues when connecting Activepieces to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Activepieces + Pydantic AI FAQ

Common questions about integrating Activepieces MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Activepieces MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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