Extracta MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Extracta through Vinkius, pass the Edge URL in the `mcps` parameter and every Extracta tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Extracta Specialist",
goal="Help users interact with Extracta effectively",
backstory=(
"You are an expert at leveraging Extracta tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Extracta "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 10 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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 Extracta MCP Server
Connect your Extracta.ai account to any AI agent and take full control of your automated data extraction and document classification through natural conversation.
When paired with CrewAI, Extracta becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Extracta tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
What you can do
- Extraction Orchestration — Create and configure new data extraction processes by defining JSON schemas for fields like dates, amounts, and item descriptions natively
- Live Document Processing — Submit publicly accessible file URLs (PDF, JPG, PNG) to trigger asynchronous extraction workflows and retrieve structured JSON data seamlessly
- AI Classification — Set up document classification rules to automatically sort documents into types like invoices, receipts, or contracts based on AI predictions
- Result Auditing — Retrieve extraction status and finalized structured data for specific documents, evaluating confidence scores and predicted categories flawlessly
- Batch History Monitoring — Fetch paginated lists of previously extracted documents and their associated data payloads to track historical processing limitlessly
- Configuration Mutation — Update existing extraction settings and mapping rules without creating new endpoints to refine your data parsing logic
- Workflow Management — View and manage extraction and classification configurations, including configured fields and webhook settings securely
The Extracta MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI 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 Extracta to CrewAI via MCP
Follow these steps to integrate the Extracta MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 10 tools from Extracta
Why Use CrewAI with the Extracta MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Extracta through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Extracta + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Extracta MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Extracta for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Extracta, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Extracta tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Extracta against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Extracta MCP Tools for CrewAI (10)
These 10 tools become available when you connect Extracta to CrewAI via MCP:
create_classification
g. invoice, receipt, contract). Pass JSON schema defining categories. Create a new Extracta document classification setup
create_extraction
g. language, format, expected fields like invoice_date, total_amount). Returns a new extractionId used for subsequent document processing. Create a new Extracta.ai data extraction process
delete_extraction
Subsequent uploads to this extractionId will fail. Delete an Extracta.ai extraction process
get_batch_results
Get bulk historical results from an Extraction process
get_classification_results
Get the predicted document category from Extracta
get_results
If not completed, it will indicate processing status. Get extraction results for a specific document
update_extraction
Modifies mapping rules without needing to create a new endpoint. Update an existing Extracta extraction configuration
upload_file_url
Returns a documentId. Use ea.get_results to poll for extracted data. Upload a document URL to Extracta for processing
view_classification
View details of an existing document classification process
view_extraction
View configuration of an existing Extracta extraction process
Example Prompts for Extracta in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Extracta immediately.
"Create an extraction process for invoices with fields: date, vendor, total"
"Extract data from this receipt URL: https://example.com/receipt.pdf"
"What type of document is doc_789 according to my classification rules?"
Troubleshooting Extracta MCP Server with CrewAI
Common issues when connecting Extracta to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Extracta + CrewAI FAQ
Common questions about integrating Extracta MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Extracta with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Extracta to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.