How to Use the LunarCrush (Social Intelligence for Crypto Assets) MCP in CrewAI

Q: How do I limit which tools my CrewAI agents can use?

Use the toolfilter option in your agent setup. This allows you to restrict your crew to only the specific tools they need from the MCP server.

Deploy a specialized crew of AI agents to monitor market sentiment using the LunarCrush MCP Server for CrewAI.

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Connect LunarCrush (Social Intelligence for Crypto Assets) MCP to CrewAI

Create your Vinkius account to connect LunarCrush (Social Intelligence for Crypto Assets) 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.

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Setup LunarCrush (Social Intelligence for Crypto Assets) with CrewAI

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Claude

Perplexity

Specialized crew research

Assign a research agent to use `list_assets` and `get_social_metrics` for your crew. They gather the data while your analyst agent interprets the results. Divide and conquer. Your agents work in tandem to process massive amounts of social intelligence, giving you a clear view of market movement.

Autonomous monitoring crews

Set your CrewAI agents to run on a loop using `get_galaxy_score` as a trigger. They monitor the market 24/7, reporting only when sentiment criteria are met. Your crew stays awake so you don't have to. They handle the monotony of data tracking while you focus on the decision-making.

Collaborative market analysis

Share the output of `get_market_metrics` across your crew's memory. Every agent has access to the same facts, leading to consistent, coordinated output. Agents talk to each other. By sharing data, your crew avoids conflicting signals and provides a unified view of the crypto landscape.

Setup guide

Set up LunarCrush (Social Intelligence for Crypto Assets) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. 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 Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke LunarCrush (Social Intelligence for Crypto Assets) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="LunarCrush (Social Intelligence for Crypto Assets) Analyst",
    goal="Access and analyze LunarCrush (Social Intelligence for Crypto Assets) data via MCP.",
    backstory="Expert analyst with direct LunarCrush (Social Intelligence for Crypto Assets) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent LunarCrush (Social Intelligence for Crypto Assets) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

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="LunarCrush (Social Intelligence for Crypto Assets) Analyst",
        goal="Access and analyze LunarCrush (Social Intelligence for Crypto Assets) data via MCP.",
        backstory="Expert analyst with direct LunarCrush (Social Intelligence for Crypto Assets) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent LunarCrush (Social Intelligence for Crypto Assets) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

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Common questions about LunarCrush (Social Intelligence for Crypto Assets) MCP in CrewAI

Pass the Vinkius endpoint URL into your CrewAI agent configuration. The framework handles the MCP connection, exposing tools to your agents automatically.

They can. Using shared memory, one agent can fetch data via the MCP server, and others can reference those results to inform their own tasks.

It works perfectly. You can set up a chain where one agent fetches data, a second performs analysis, and a third creates a summary for your review.

Use the tool_filter option in your agent setup. This allows you to restrict your crew to only the specific tools they need from the MCP server.

The server uses isolated memory for each agent session. Your asset list and query history are discarded after each task completion to ensure absolute privacy.

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