How to Use the EODHD Financial MCP in CrewAI
Deploy specialized multi-agent teams in CrewAI to research global stocks and track corporate actions automatically.
Works with every AI agent you already use
…and any MCP-compatible client
Connect EODHD Financial MCP to CrewAI
Create your Vinkius account to connect EODHD Financial 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.
Multi-agent fundamental research teams
`get_fundamentals` supplies deep financial metrics to your research agent while another agent analyzes the valuation. The CrewAI framework allows these specialized agents to collaborate and share memory during the analysis. One agent can fetch the raw data while a second agent writes the investment memo. This division of labor keeps your research process structured and highly detailed.
Collaborative dividend and split tracking
`get_historical_dividends` fetches historical payouts for a list of stocks while a separate auditing agent checks for splits using `get_splits`. The agents pass these data points back and forth to build an adjusted yield report. This collaborative execution ensures that corporate actions are analyzed in context. Your agents work sequentially, ensuring the dividend yield calculations account for recent stock splits.
Autonomous market scanning via this MCP Server
`search_tickers` allows a discovery agent to find the exact symbol format for any company name. Once found, the agent passes the correct TICKER.EXCHANGE string to a pricing agent to verify current market activity. The entire process runs autonomously within your CrewAI team. You define the roles, and the agents execute the search, validation, and pricing steps without human intervention.
Set up EODHD Financial MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke EODHD Financial tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="EODHD Financial Analyst",
goal="Access and analyze EODHD Financial data via MCP.",
backstory="Expert analyst with direct EODHD Financial access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent EODHD Financial transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="EODHD Financial Analyst",
goal="Access and analyze EODHD Financial data via MCP.",
backstory="Expert analyst with direct EODHD Financial access.",
tools=mcp_tools,
)
task = Task(
description="List recent EODHD Financial transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EODHD Financial Data. 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 EODHD Financial MCP in CrewAI
Use it with your favorite AI tools
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