How to Use the Goldsky (Web3 Data Indexing & Subgraphs) MCP in CrewAI

Q: How do I filter tools for specific agents?

You use the toolfilter option in your agent configuration. Only the agents you authorize get access to the indexing tools.

Deploy a specialized agent crew to manage high-throughput Web3 indexing with Goldsky (Web3 Data Indexing & Subgraphs).

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Connect Goldsky (Web3 Data Indexing & Subgraphs) MCP to CrewAI

Create your Vinkius account to connect Goldsky (Web3 Data Indexing & Subgraphs) 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 Goldsky (Web3 Data Indexing & Subgraphs) with CrewAI

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Claude

Perplexity

Multi-Agent Indexing Control in CrewAI

Assign a monitor agent to watch pipeline health while a moderator agent takes action. They share memory to coordinate `get_pipeline_state` checks. It creates a division of labor. One agent watches the logs, the other manages the lifecycle.

Hierarchical Pipeline Management in CrewAI

Structure your crew to handle complex indexing tasks. Use sequential execution to validate, deploy, and verify pipelines using `create_pipeline`. It ensures every step finishes before the next one starts. Your infrastructure deployment becomes a predictable process.

Autonomous Incident Response in CrewAI

Let your crew respond to outages without human input. An agent uses `get_pipeline_logs` to diagnose errors and then attempts a fix. It reduces the time you spend debugging. Your agents handle the common failure cases automatically.

Setup guide

Set up Goldsky (Web3 Data Indexing & Subgraphs) 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 Goldsky (Web3 Data Indexing & Subgraphs) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Goldsky (Web3 Data Indexing & Subgraphs) Analyst",
    goal="Access and analyze Goldsky (Web3 Data Indexing & Subgraphs) data via MCP.",
    backstory="Expert analyst with direct Goldsky (Web3 Data Indexing & Subgraphs) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Goldsky (Web3 Data Indexing & Subgraphs) 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 →

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="Goldsky (Web3 Data Indexing & Subgraphs) Analyst",
        goal="Access and analyze Goldsky (Web3 Data Indexing & Subgraphs) data via MCP.",
        backstory="Expert analyst with direct Goldsky (Web3 Data Indexing & Subgraphs) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Goldsky (Web3 Data Indexing & Subgraphs) 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 Goldsky. 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 Goldsky (Web3 Data Indexing & Subgraphs) MCP in CrewAI

You pass the server URL to your agents in the crew setup. The agents treat the indexing tools as their own internal knowledge base.

They can. You define a crew with specific roles like 'Indexer' and 'Monitor'. They collaborate to keep your data pipelines running.

They are. You provide the token to the server connection. It never leaves the secure transport between your crew and the host.

You use the tool_filter option in your agent configuration. Only the agents you authorize get access to the indexing tools.

The agents retrieve raw logs and state data. This information is processed within the crew's memory to make decisions about infrastructure health.

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