XBRL (eXtensible Business Reporting Language) is a standardized format for financial data required by the SEC since 2009. It tags every financial number (revenue, assets, debt, etc.) with a machine-readable label, making it possible to extract and compare financial data across companies automatically.

What is a US-GAAP concept?

US-GAAP comprises the standard accounting principles in the US. Each accounting term (like 'Revenues' or 'NetIncomeLoss') maps directly to specific facts filed in XBRL format.

The SEC provides 'Frames' to view an entire industry's metric at once (e.g., all revenues in Q1 2024) instead of polling company-by-company.

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison through the Vinkius — pass the Edge URL in the `mcps` parameter and every SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison Specialist",
    goal="Help users interact with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison effectively",
    backstory=(
        "You are an expert at leveraging SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

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

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison

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About SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server

SEC XBRL financial data.

When paired with CrewAI, SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

4 Tools

Key Financials — Revenue, income, assets, EPS, cash
Financial Metric — Any US-GAAP concept
All Facts — Complete XBRL data dump
Industry Comparison — Cross-company metric frames

Zero Auth

Like a free Bloomberg terminal

The SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server exposes 4 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to CrewAI via MCP

Follow these steps to integrate the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 4 tools from SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison

Why Use CrewAI with the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 the 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

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison + CrewAI Use Cases

Practical scenarios where CrewAI combined with the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Tools for CrewAI (4)

These 4 tools become available when you connect SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to CrewAI via MCP:

get_all_company_facts

This is the raw, comprehensive dataset — hundreds of concepts across multiple years. Use get_key_financials for a curated summary, or this for deep analysis. Get ALL XBRL financial facts for a company — complete financial data dump

get_financial_metric

Common concepts: Revenues, NetIncomeLoss, Assets, Liabilities, StockholdersEquity, EarningsPerShareBasic, LongTermDebt, ResearchAndDevelopmentExpense, CashAndCashEquivalentsAtCarryingValue, CommonStockSharesOutstanding. If the concept is not found, returns available concepts. Get a specific US-GAAP financial concept for a company (e.g., Revenue, Debt, R&D)

get_industry_comparison

Useful for industry comparison and screening. Example: get all companies' Revenue for CY2024. Period format: CY2024 (annual), CY2024Q1 (quarterly), CY2024Q1I (instant). Compare a financial metric across ALL companies — industry-wide XBRL frame data

get_key_financials

Returns the most recent 5 reported values across 10-K and 10-Q filings. This is like a mini Bloomberg terminal — for free. Get key financial data for a company — revenue, net income, assets, equity, EPS, cash

Example Prompts for SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison immediately.

"Get Apple's key financial data — revenue, income, assets, and EPS"

"What is Meta's exact Research and Development Expense?"

"Show me a comparison of Revenue across all companies for CY2024"

Troubleshooting SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server with CrewAI

Common issues when connecting SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison + CrewAI FAQ

Common questions about integrating SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard 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?

Yes. Each agent has its own 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?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using 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)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.