How do I get a Pipefy API token and where do I find it?

Log in to Pipefy, click on your **Profile icon** (top-right), go to **Profile > API Access**, and generate a new token. Alternatively, use **Service Accounts** for team-based access. Copy the token immediately — it starts with `eyJhbG...`. Paste it into the API token field below. This token authenticates all GraphQL API requests to `https://api.pipefy.com/graphql`.

How do I move a card from one phase to another in a pipe?

Use the `move_card_to_phase` tool with the card_id (from list_cards or get_card) and the target phase_id (from get_pipe or list_phases). This advances the card through your workflow. For example, moving a card from 'New Requests' to 'In Review' phase. The card retains all its field values after moving. This is the primary way to progress items through your process.

Can I search for cards by a specific field value like email or customer name?

Yes! Use the `search_cards_by_field` tool with the pipe_id, field_id (the specific field to search in), and search_value (the text to find). This searches all cards in the pipe where that field contains your search text. It's perfect for finding cards by customer email, name, order number, or any custom field. Results include full card details with all field values.

How do I create a new card with custom field values?

Use the `create_card` tool with the pipe_id and a JSON object containing field values. The fields parameter should be a JSON object where keys are field IDs (from get_pipe) and values are the data to store. Example: `{ "name": "John Doe", "email": "john@example.com", "priority": "High" }`. You can also optionally specify a phase_id to start the card in a specific phase instead of the default first phase.

Pipefy MCP Server for AutoGen 14 tools — connect in under 2 minutes

Name: Pipefy
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 14 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Pipefy as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="pipefy_agent",
            tools=tools,
            system_message=(
                "You help users with Pipefy. "
                "14 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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* 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 Pipefy MCP Server

Connect your Pipefy account to any AI agent and take full control of your process management workflows through natural conversation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Pipefy tools. Connect 14 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Pipe Discovery — List all pipes (processes) in your organization and inspect their structure, phases, and fields
Card Management — Create, read, update, and delete cards (items/records) flowing through your pipes
Field Updates — Update specific field values on existing cards as information changes or processes evolve
Phase Transitions — Move cards between phases to advance workflow steps (e.g., New → In Progress → Done)
Card Search — Search for cards by field value to find specific items by email, name, ID, or custom data
Card Cloning — Duplicate existing cards to quickly create similar items with pre-filled field values
Organization Info — View organization details, members, and available pipes
User Profile — Check your authenticated user profile and organization memberships

The Pipefy MCP Server exposes 14 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Pipefy to AutoGen via MCP

Follow these steps to integrate the Pipefy MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 14 tools from Pipefy automatically

Why Use AutoGen with the Pipefy MCP Server

AutoGen provides unique advantages when paired with Pipefy through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Pipefy tools to solve complex tasks

Role-based architecture lets you assign Pipefy tool access to specific agents — a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Pipefy tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Pipefy tool responses in an isolated environment

Pipefy + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Pipefy MCP Server delivers measurable value.

Collaborative analysis: one agent queries Pipefy while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Pipefy, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Pipefy data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Pipefy responses in a sandboxed execution environment

Pipefy MCP Tools for AutoGen (14)

These 14 tools become available when you connect Pipefy to AutoGen via MCP:

clone_card

You must provide the card_id of the card to clone. The new card is created in the same pipe as the original, starting at the first phase. This is useful for creating similar requests, repeating processes, or using an existing card as a template for new items. The cloned card gets a new unique ID but retains all field data. Clone an existing card to create a duplicate

create_card

You must provide the pipe_id and a JSON object containing field values matching the pipe's required fields. Fields are key-value pairs where keys are field IDs and values are the data to store. Optionally specify a phase_id to start the card in a specific phase (defaults to first phase). Example fields: { "name": "John Doe", "email": "john@example.com", "priority": "High" } Create a new card in a Pipefy pipe

delete_card

You must provide the card_id. This action cannot be undone. Use this to remove test cards, duplicates, or items that were created in error. Be careful as this will also remove all associated data including comments, attachments, and field values for that card. Delete a card from a pipe

get_card

Use the card_id obtained from list_cards to inspect full card information. This is useful for reviewing card details before updating fields or moving to another phase. Get detailed information about a specific card

get_organization

Use the organization_id to inspect your organization's structure, understand team membership, and discover available pipes for card management. Get details of a Pipefy organization

get_phase

Phases represent steps in a pipe's workflow. Use the phase_id obtained from get_pipe or list_phases to inspect phase configuration. This helps understand what fields are required at each step of the workflow. Get details of a specific phase

get_pipe

Each pipe represents a workflow or process with multiple phases (steps) and custom fields. Use the pipe_id to get the structure of a pipe before creating cards or managing cards within it. The response includes all phases with their IDs, names, and the custom fields defined for the pipe. Get details of a specific Pipefy pipe (process)

get_user_profile

Use this to verify API token access and discover organization IDs needed for other queries. This is also useful for understanding which organizations and pipes the user has access to. Get the authenticated user profile

list_cards

Cards represent individual items flowing through the pipe's workflow phases (e.g., requests, tasks, tickets, leads). You must provide the pipe_id. Optionally filter by phase_id to see cards in a specific phase. Each card includes title, current phase, completion status, due date, and assignees. Use this to monitor workflow progress and identify cards that need attention. List all cards in a pipe with optional phase filter

list_phases

Each phase represents a stage that cards flow through in the process. Use this to understand the workflow structure and identify phase IDs for filtering cards or moving cards between phases. The response includes phase names and card counts. List all phases in a pipe

list_pipes

Each pipe represents a structured workflow with phases, fields, and cards. You must provide the organization_id which can be found in your Pipefy URL or obtained from get_user_profile. Use this to discover all available pipes before managing cards within them. List all pipes in an organization

move_card_to_phase

You must provide the card_id and the target phase_id. This is the primary way to advance workflow items through the pipe's process steps. Common use cases: moving a request from "New" to "In Review", advancing a lead to "Qualified", or progressing a task to "Completed". The card retains all its field values after moving. Move a card to a different phase in the pipe

search_cards_by_field

This is useful for finding cards by email, name, ID, or any custom field content. You must provide the pipe_id, field_id (the field to search in), and search_value (text to find). Results include card title, current phase, status, and all field values for matching cards. The search uses a "contains" operator for flexible matching. Search cards in a pipe by a specific field value

update_card_field

You must provide the card_id, the field_id of the field to update, and the new value as a string. This is useful for updating card information as requests progress or details change. Common updates: changing priority, updating contact info, modifying descriptions, or setting dates. Update a specific field value on a card

Example Prompts for Pipefy in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Pipefy immediately.

"List all pipes in my organization and show me the cards in the 'IT Support' pipe."

"Create a new purchase request card in the Purchase Requests pipe with these details: Requester: Maria Silva, Item: MacBook Pro 16", Quantity: 2, Justification: Design team replacement."

"Search for all cards in the IT Support pipe where the email field contains 'john@company.com' and show me their current status."

Troubleshooting Pipefy MCP Server with AutoGen

Common issues when connecting Pipefy to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Pipefy + AutoGen FAQ

Common questions about integrating Pipefy MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Pipefy tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.