How to Use the PDF Munk MCP in CrewAI

Q: How to configure PDF Munk as a tool in CrewAI?

Provide the MCP server URL in your agent's mcps list. The crew will automatically gain access to all document tools.

Coordinate specialized agents in CrewAI to manage your entire document lifecycle.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect PDF Munk MCP to CrewAI

Create your Vinkius account to connect PDF Munk to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PDF Munk with CrewAI

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Collaborative PDF tasks in CrewAI

Assign a research agent to fetch content and a processing agent to run `generate_pdf_from_html`. They share memory to finish the job. This setup allows one agent to prepare the data and another to format it. You get a finished file without manual oversight.

Automated document archival with CrewAI

Use `compress_pdf` as a final step in your crew's workflow. It shrinks your files before they hit your storage buckets. Your agents handle the heavy lifting. They ensure the files are ready for delivery once the task is marked complete.

Status verification for autonomous crews

Have your monitor agent call `check_pdfmunk_status` before starting a job. If the service is down, the crew pauses or alerts you. It adds a layer of intelligence to your autonomous operations. Your agents act only when the environment is ready.

Setup guide

Set up PDF Munk MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke PDF Munk tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="PDF Munk Analyst",
    goal="Access and analyze PDF Munk data via MCP.",
    backstory="Expert analyst with direct PDF Munk access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent PDF Munk transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="PDF Munk Analyst",
        goal="Access and analyze PDF Munk data via MCP.",
        backstory="Expert analyst with direct PDF Munk access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent PDF Munk transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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