How to Use the Blockchair (Universal Blockchain Search Engine & API) MCP in CrewAI
Deploy specialized agent crews to monitor and act on blockchain data with this MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Blockchair (Universal Blockchain Search Engine & API) MCP to CrewAI
Create your Vinkius account to connect Blockchair (Universal Blockchain Search Engine & API) 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.
Collaborative blockchain research in CrewAI
Assign research agents to use `get_block` and `get_transaction` for deep dives. The crew shares this memory so the analyst agent has the context it needs. Your agents work in sequence. One finds the raw data, the other writes the summary report.
Autonomous monitoring with CrewAI
Let a monitor agent track address activity using `get_address`. If it sees an anomaly, it passes the data to a moderator agent to take action. You define the rules of engagement. The crew handles the constant checking while you focus on the results.
Escalation workflows in CrewAI
Configure your agents to broadcast transactions via `push_transaction` only after a verification agent approves the payload. It creates a secure pipeline for your operations. No action hits the network without meeting the standards you set for your crew.
Set up Blockchair (Universal Blockchain Search Engine & API) 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 Blockchair (Universal Blockchain Search Engine & API) tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Blockchair (Universal Blockchain Search Engine & API) Analyst",
goal="Access and analyze Blockchair (Universal Blockchain Search Engine & API) data via MCP.",
backstory="Expert analyst with direct Blockchair (Universal Blockchain Search Engine & API) access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Blockchair (Universal Blockchain Search Engine & API) 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="Blockchair (Universal Blockchain Search Engine & API) Analyst",
goal="Access and analyze Blockchair (Universal Blockchain Search Engine & API) data via MCP.",
backstory="Expert analyst with direct Blockchair (Universal Blockchain Search Engine & API) access.",
tools=mcp_tools,
)
task = Task(
description="List recent Blockchair (Universal Blockchain Search Engine & API) 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 Blockchair. 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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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
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Common questions about Blockchair (Universal Blockchain Search Engine & API) MCP in CrewAI
Use it with your favorite AI tools
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Start using the Blockchair (Universal Blockchain Search Engine & API) MCP today
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