How to Use the MyScale (SQL Vector Database API) MCP in CrewAI

Q: How do I install MyScale (SQL Vector Database API) tools in CrewAI?

Install crewai and pass the Vinkius MCP Server URL directly into your agent's mcps array. For advanced setups, use MCPServerHTTP to filter which tools are exposed to specific agents.

Q: Can a CrewAI agent create tables in MyScale (SQL Vector Database API) dynamically?

Yes. Assign the createvectortable tool to a specialized database administrator agent. The agent will execute the table creation and verify the schema before other agents start writing data.

Q: How do agents coordinate vector search and SQL queries using MyScale (SQL Vector Database API) in CrewAI?

One agent can run vectorsearch to get semantic matches, and then pass those document IDs to another agent. The second agent uses executesqlquery to pull the full relational metadata and compile the final report.

Deploy multi-agent teams to manage and search your database using CrewAI and our MCP Server.

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Connect MyScale (SQL Vector Database API) MCP to CrewAI

Create your Vinkius account to connect MyScale (SQL Vector Database 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.

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Setup MyScale (SQL Vector Database API) with CrewAI

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Assign database tasks to specialized CrewAI agents

The `execute_sql_query` tool gives your data analyst agent the ability to run raw SQL directly. This agent can fetch metadata, join tables, and clean up dirty records without human intervention. Meanwhile, a researcher agent can use `vector_search` to find relevant documents. Because CrewAI supports shared memory, the analyst and researcher coordinate their findings to produce a single, unified report.

Let agents manage database indices autonomously

The `create_vector_index` tool allows a DBA agent to build indices when database performance drops. The agent monitors the index build using `check_index_status` to ensure it completes successfully before running searches. This removes the burden of manual database tuning. Your autonomous crew handles the heavy lifting of index maintenance based on real-time performance needs.

Run pre-flight cluster checks in your MCP Server

The `ping_cluster` tool lets your coordinator agent verify that the database is reachable before starting a multi-step job. If the connection fails, the coordinator halts the crew and escalates the issue. This prevents your agents from wasting API credits on queries that cannot be executed. It acts as a guardrail for your autonomous teams.

Setup guide

Set up MyScale (SQL Vector Database API) 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 MyScale (SQL Vector Database API) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent MyScale (SQL Vector Database API) 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="MyScale (SQL Vector Database API) Analyst",
        goal="Access and analyze MyScale (SQL Vector Database API) data via MCP.",
        backstory="Expert analyst with direct MyScale (SQL Vector Database API) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent MyScale (SQL Vector Database API) 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 MyScale. 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 MyScale (SQL Vector Database API) MCP in CrewAI

Install `crewai` and pass the Vinkius MCP Server URL directly into your agent's `mcps` array. For advanced setups, use `MCPServerHTTP` to filter which tools are exposed to specific agents.

Yes. Assign the `create_vector_table` tool to a specialized database administrator agent. The agent will execute the table creation and verify the schema before other agents start writing data.

One agent can run `vector_search` to get semantic matches, and then pass those document IDs to another agent. The second agent uses `execute_sql_query` to pull the full relational metadata and compile the final report.

Yes. This MCP Server supports stdio, SSE, and Streamable HTTP. You can configure the transport method that best fits your CrewAI deployment environment.

This MCP Server protects your high-dimensional vector arrays and SQL query structures by processing them within a secure, ephemeral V8 isolate. Vinkius handles the database authentication token exchange server-side, ensuring your raw database credentials never leak to the local CrewAI runtimes.

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