How to Use the Crystal Matcher MCP in CrewAI

Q: Is Crystal Matcher suitable for CrewAI's multi-agent setup?

It’s perfect for it. You can assign different tools—like filtercrystalsbyelement and querycrystalsbyintent—to specialized agents, letting them work together toward a single goal.

Run autonomous crystal research with CrewAI multi-agent teams.

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Connect Crystal Matcher MCP to CrewAI

Create your Vinkius account to connect Crystal Matcher 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 Crystal Matcher with CrewAI

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Your setup doesn't run one agent; it runs a team. The 'Researcher Agent' can use `query_crystals_by_intent` to gather initial ideas, while the 'Analyzer Agent' takes over to validate those findings. This specialized collaboration handles complex matching that no single AI client could manage.

Coordinated filtering and verification

Need a deep dive? The team can be structured: one agent uses `find_crystals_by_chakra` to get the list, and another dedicated 'Validator Agent' then calls `get_crystal_details` on each result. This specialized handoff ensures thorough checking. The entire operation is monitored by a central coordinator agent.

Sequential knowledge retrieval

You can set up roles where the 'Planner Agent' determines if an element filter is needed, and then passes control to the 'Executor Agent' which uses `filter_crystals_by_element`. This sequential, role-based execution means you get highly specific results without needing constant human intervention.

Setup guide

Set up Crystal Matcher 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 Crystal Matcher tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Crystal Matcher 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 Crystal Matcher. 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 Crystal Matcher MCP in CrewAI

CrewAI lets specialized agents collaborate on the matching process. One agent gathers data using `query_crystals_by_intent`, and another processes that output to provide a final, validated recommendation.

Yes. You can define an entire workflow where specialized agents handle the crystal matching—from initial search using `find_crystals_by_chakra` to final reporting using `get_crystal_details`.

The MCP only touches catalog details, including specific information on elements and chakras. No personal or identifying user data is ever exposed to the agents.

It’s perfect for it. You can assign different tools—like `filter_crystals_by_element` and `query_crystals_by_intent`—to specialized agents, letting them work together toward a single goal.

The flow is managed by the crew structure. Agent A gets results from `find_crystals_by_chakra`, passes those IDs to Agent B, which then uses `get_crystal_details` for final output.

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