How to Use the Affinda MCP in CrewAI

Q: How do I connect the Affinda MCP Server to a CrewAI agent?

Pass your Vinkius HTTP URL directly into the agent's mcps array during initialization. CrewAI automatically discovers tools like createdocument and makes them available to the agent.

Q: Can a CrewAI agent autonomously choose the right Affinda parser?

Yes, your agent can call listdocumenttypes to see if a resume or invoice parser is available. It then routes the document to the correct parser based on its analysis of the file.

Q: How do multiple CrewAI agents share Affinda document data?

Agents share the document ID retrieved from createdocument through CrewAI's shared memory over MCP. The analysis agent then uses getdocument to pull the structured JSON and continue the task.

Run autonomous multi-agent crews that parse, analyze, and file invoices with CrewAI and the Affinda MCP Server.

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Connect Affinda MCP to CrewAI

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

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Setup Affinda with CrewAI

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Multi-agent document ingestion using CrewAI

The `create_document` tool allows your ingestion agent to upload resumes or invoices autonomously. Once uploaded, a separate analysis agent takes over to verify the extracted fields. This cooperative behavior is native to CrewAI when connected to the MCP Server. One agent handles the API communication while another validates the output data.

Hierarchical workspace audits with CrewAI teams

The `list_workspaces` tool gives your manager agent a complete view of all document containers. The manager agent then delegates specific workspaces to worker agents for auditing. Worker agents use `list_documents` to find unprocessed files and execute validation tasks. This hierarchical setup keeps your document pipelines organized without manual intervention.

Autonomous validation and record checking

The `get_document` tool lets your verification agent pull structured JSON data for deep analysis. The agent compares the parsed fields against your internal database to flag discrepancies. Before running the extraction, the crew uses `list_document_types` to verify that the correct parser is active. This prevents errors when processing mixed batches of passports and invoices.

Setup guide

Set up Affinda 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 Affinda tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Affinda 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="Affinda Analyst",
        goal="Access and analyze Affinda data via MCP.",
        backstory="Expert analyst with direct Affinda access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Affinda 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Affinda. 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.

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Common questions about Affinda MCP in CrewAI

Pass your Vinkius HTTP URL directly into the agent's `mcps` array during initialization. CrewAI automatically discovers tools like `create_document` and makes them available to the agent.

Yes, your agent can call `list_document_types` to see if a resume or invoice parser is available. It then routes the document to the correct parser based on its analysis of the file.

Agents share the document ID retrieved from `create_document` through CrewAI's shared memory over MCP. The analysis agent then uses `get_document` to pull the structured JSON and continue the task.

Yes, you can deploy multiple specialized agents to process different workspaces simultaneously. They use the server's tools to query and update files in parallel.

All document processing runs through ephemeral V8 isolates on Vinkius. Your sensitive PDFs and images are processed in memory and never written to persistent disk storage on the platform.

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