Intrinio MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Intrinio through Vinkius, pass the Edge URL in the `mcps` parameter and every Intrinio 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="Intrinio Specialist",
goal="Help users interact with Intrinio effectively",
backstory=(
"You are an expert at leveraging Intrinio 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 Intrinio "
"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 Intrinio MCP Server
Empower your AI agents with Intrinio's comprehensive financial data. This MCP server allows you to retrieve real-time and historical stock prices, access financial statements, search for companies, and track earnings releases and IPO calendars directly through the Intrinio API. Ideal for financial analysis, portfolio monitoring, and market research.
When paired with CrewAI, Intrinio becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Intrinio tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
The Intrinio 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 Intrinio to CrewAI via MCP
Follow these steps to integrate the Intrinio 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 Intrinio
Why Use CrewAI with the Intrinio MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Intrinio 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
Intrinio + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Intrinio MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Intrinio 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 Intrinio, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Intrinio 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 Intrinio against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Intrinio MCP Tools for CrewAI (10)
These 10 tools become available when you connect Intrinio to CrewAI via MCP:
get_company
g., "AAPL") or ID. Returns headquarters address, employee counts, and business descriptions. Useful for providing a profile overview of a company. Retrieves details for a specific company
get_earnings_releases
Essential for tracking reporting seasons and anticipating market volatility for specific tickers. Lists upcoming and past earnings releases
get_financials
Returns line items and values. Essential for fundamental financial analysis and performance vetting. Retrieves financial statements for a company
get_ipo_calendar
Useful for identifying new market entrants and investment opportunities. Retrieves the IPO calendar
get_security
Returns exchange info, security type, and identifiers. Use this to distinguish between different types of instruments traded under similar names. Retrieves details for a specific security
get_stock_prices
Use this to analyze market performance and price trends over time. Retrieves historical stock prices for a security
list_companies
Returns company names, tickers, and internal IDs. Use this to discover tickers before querying specific stock prices or financial statements. Lists all companies covered by Intrinio
list_indices
g., S&P 500, Dow Jones) tracked by Intrinio. Use this to identify index identifiers before querying index performance data. Lists stock market indices
list_news
Useful for monitoring market-moving events and recent announcements from public companies. Lists latest financial news
search_companies
Use this when the user provided a partial company name and you need to locate the correct ticker or ID. Searches for companies by name or ticker
Example Prompts for Intrinio in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Intrinio immediately.
"List financial statements for Apple (AAPL)."
"Get the latest stock price for Microsoft."
"Search for companies in the 'Software' industry."
Troubleshooting Intrinio MCP Server with CrewAI
Common issues when connecting Intrinio 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
Intrinio + CrewAI FAQ
Common questions about integrating Intrinio 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 Intrinio with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
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 Intrinio to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.