How to Use the Couchbase (Vector & NoSQL) MCP in CrewAI

Q: How do I filter Couchbase (Vector & NoSQL) tools for specific CrewAI agents?

Use the toolfilter option in your agent definition. This restricts which tools an agent can use, keeping your operations focused.

Deploy a crew of specialized agents to manage Couchbase (Vector & NoSQL) operations.

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Connect Couchbase (Vector & NoSQL) MCP to CrewAI

Create your Vinkius account to connect Couchbase (Vector & NoSQL) 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 Couchbase (Vector & NoSQL) with CrewAI

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Couchbase (Vector & NoSQL) research crews for CrewAI

Assign a researcher agent to run `fts_search` and `get_document` while a secondary agent analyzes the results. They work in tandem to pull insights without your input. This split-role approach makes your data analysis faster. One agent digs for facts while the other structures them for your report.

Autonomous Couchbase (Vector & NoSQL) agents in CrewAI

Set up a monitor agent to watch for specific data patterns using `execute_n1ql_query`. If the agent finds a match, it triggers a response sequence. It automates your database oversight. You spend less time checking logs and more time acting on the findings.

CrewAI agents mapping Couchbase (Vector & NoSQL) spaces

Use `list_buckets` and `list_scopes` to let your agents map the entire database layout. They use this map to navigate complex data environments autonomously. This gives your crew full situational awareness. They don't get lost in large datasets because they can see the boundaries.

Setup guide

Set up Couchbase (Vector & NoSQL) 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 Couchbase (Vector & NoSQL) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Couchbase (Vector & NoSQL) 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 Couchbase. 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 Couchbase (Vector & NoSQL) MCP in CrewAI

Yes, the agents share memory. Once one agent retrieves data, the rest of the crew can access it for their specific tasks.

Use the tool_filter option in your agent definition. This restricts which tools an agent can use, keeping your operations focused.

Hierarchical execution works perfectly. A manager agent can delegate database lookups to subordinate agents based on the task requirements.

You can connect via HTTP or stdio transports. The setup handles the connection for your agents so they can perform operations reliably.

Access is scoped to the specific endpoint token provided. The server enforces strict isolation, ensuring only authorized agents touch your database.

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