How to Use the Azure Cosmos DB Container MCP in CrewAI

Q: How do I pass the Azure Cosmos DB Container tools to my CrewAI agents?

Install crewaitools. Add the Vinkius endpoint directly to the mcps parameter when defining your Agent. The framework handles the connection automatically.

Q: Can I restrict which CrewAI agents can delete from the Azure Cosmos DB Container?

Yes. Import MCPServerHTTP from crewai.mcp. Use the toolfilter argument to expose deletedocument only to your admin agents.

Equip your CrewAI agents with a dedicated NoSQL database. Let specialized workers read and write Cosmos DB records autonomously.

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Connect Azure Cosmos DB Container MCP to CrewAI

Create your Vinkius account to connect Azure Cosmos DB Container 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 Azure Cosmos DB Container with CrewAI

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Perplexity

Autonomous NoSQL Operations via MCP Server

You don't want a single script doing everything. Assign this MCP Server toolset to a specialized database worker. A researcher agent finds information, and your database agent uses `create_document` to commit the structured JSON into your container. They share context through the framework's memory. The database worker knows exactly which partition key to use because the researcher found it. You just pass the Vinkius URL into the mcps array to get them talking.

Cross-Checking Live Records

Before a moderator agent takes action, it needs facts. It can call `get_document` to pull the exact state of a user profile or transaction. It feeds that JSON payload back into the crew's shared context. If the record requires updating, another agent takes over. This separation of concerns keeps your autonomous operations predictable.

Complex Data Audits

Sometimes a crew needs to analyze bulk data. A dedicated analyst agent can run `query_documents` to pull specific subsets of your container. It executes raw SQL like "SELECT * FROM c WHERE c.flagged = true" and processes the results. For tighter control, use MCPServerHTTP with a tool_filter. You can restrict the analyst to only run queries, while completely hiding the `delete_document` tool from its available actions.

Setup guide

Set up Azure Cosmos DB Container 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 Azure Cosmos DB Container tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Azure Cosmos DB Container 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 Azure Cosmos DB Container. 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 Azure Cosmos DB Container MCP in CrewAI

Install crewai[tools]. Add the Vinkius endpoint directly to the mcps parameter when defining your Agent. The framework handles the connection automatically.

Yes. Import MCPServerHTTP from crewai.mcp. Use the tool_filter argument to expose `delete_document` only to your admin agents.

No. The database logic runs entirely on the remote Vinkius infrastructure. Your local Python environment just makes HTTP calls to the provided endpoint.

The agent reads the tool schema and knows when a partition key is required. Make sure your crew's prompt instructs them to gather the partition key before calling the fetch or delete tools.

Vinkius operates on a zero-trust model. Your SQL queries, JSON document payloads, and database IDs exist only during the brief execution window. The ephemeral sandbox tears down the moment the CrewAI worker receives its data.

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