How to Use the Arcsecond.io MCP in CrewAI

Q: How do I configure CrewAI to use the Arcsecond.io MCP Server?

Run pip install crewai "crewaitools". For a basic setup, pass the endpoint directly via mcps="https://..." in your agent definition. Advanced users should import MCPServerHTTP from crewai.mcp to apply a toolfilter.

Q: Can I assign specific Arcsecond.io tools to different CrewAI agents?

Yes. Use the toolfilter configuration. You give the researcher agent the search tools and restrict the monitor agent to the observatory listing tools exposed by the MCP Server.

Deploy autonomous astronomical research teams using CrewAI and the Arcsecond.io MCP Server.

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Setup Arcsecond.io with CrewAI

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Perplexity

Multi-agent observatory monitoring

Your dedicated hardware monitor agent runs `list_telescopes` on a loop to check equipment status across multiple facilities. One agent cannot watch everything, so CrewAI lets you specialize. You build a team to handle the load. Meanwhile, a separate logistics agent maps the physical infrastructure using `list_observing_sites`. They share a memory pool. When the monitor detects a telescope failure, the logistics agent immediately knows exactly which site requires maintenance.

Autonomous night log analysis

You can assign an analyst agent to run `list_night_logs` every morning to automate hours of manual review. It reads through the metadata to find anomalies or missed targets. Humans no longer need to parse raw JSON logs. If the analyst spots something interesting, it triggers a researcher agent. That second agent uses `list_datasets` to pull the actual raw files from the observatory. The entire process happens autonomously while you sleep.

Collaborative celestial object research

Your scout agent executes `search_objects` to build a preliminary list of candidates based on loose criteria. Finding specific stars requires cross-referencing multiple databases. The scout does the initial heavy lifting. The scout hands that list to a verification agent. This specialist uses `get_object` to pull the precise coordinates and spectral data via the MCP Server. The agents debate the results and output a single, verified JSON report.

Setup guide

Set up Arcsecond.io 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 Arcsecond.io tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Arcsecond.io 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="Arcsecond.io Analyst",
        goal="Access and analyze Arcsecond.io data via MCP.",
        backstory="Expert analyst with direct Arcsecond.io access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Arcsecond.io 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Arcsecond.io. 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 Arcsecond.io MCP in CrewAI

Run `pip install crewai "crewai[tools]"`. For a basic setup, pass the endpoint directly via `mcps=["https://..."]` in your agent definition. Advanced users should import `MCPServerHTTP` from `crewai.mcp` to apply a `tool_filter`.

Yes. Use the `tool_filter` configuration. You give the researcher agent the search tools and restrict the monitor agent to the observatory listing tools exposed by the MCP Server.

Agents write their findings to a shared context window. When one agent finds a star system, the other agents can read those coordinates without needing to run the search tool again.

CrewAI agents can self-correct. If the tool returns an error, the agent reads the error message, adjusts its parameters, and tries the request again.

Your site locations and hardware specs remain private. The server executes inside an ephemeral V8 sandbox. Vinkius destroys the execution environment the moment the tool call finishes.

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