Can my agent perform K-Nearest Neighbor (KNN) vector searches in Couchbase?

Yes. Provide the search index name, the vector embedding array, and the number of results (k). The agent uses Couchbase's native vector capabilities to locate the most semantically similar documents in your cluster.

How do I execute a N1QL query through the agent?

Use the 'execute_n1ql_query' tool and provide your SQL-like statement. The agent will fetch the structural JSON blocks directly from Couchbase, allowing you to perform complex data retrieval using familiar SQL syntax.

Can I search documents using full-text query logic?

Absolutely. The 'fts_search' tool leverages Couchbase's Full-Text Search (FTS) engine. Provide an index name and a boolean query string to perform structural text-based extraction across your document trees.

Couchbase (Vector & NoSQL) MCP Server for OpenAI Agents SDK 7 tools — connect in under 2 minutes

Name: Couchbase (Vector & NoSQL)
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 7 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Couchbase (Vector & NoSQL) through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Couchbase (Vector & NoSQL) Assistant",
            instructions=(
                "You help users interact with Couchbase (Vector & NoSQL). "
                "You have access to 7 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Couchbase (Vector & NoSQL)"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Couchbase (Vector & NoSQL) MCP Server

Connect your Couchbase (Capella or self-hosted) cluster to any AI agent and take full control of your NoSQL and vector data through natural conversation.

The OpenAI Agents SDK auto-discovers all 7 tools from Couchbase (Vector & NoSQL) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Couchbase (Vector & NoSQL), another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Vector Search (KNN) — Execute direct searches mapping AI embeddings to locate textual similarities using native vector indices
N1QL SQL-for-JSON — Push absolute explicit querying using N1QL (SQL for Couchbase) to retrieve complex JSON structures across your buckets
Document CRUD — Fetch elaborate internal properties and retrieve exact Data maps from specific collections using unique document keys
Full-Text Search (FTS) — Perform structural text-based extraction matching query strings across advanced FTS search indexes
Schema Navigation — Identify bounded routing spaces including Buckets, Scopes, and Collections to understand your data organization
Index Auditing — Enumerate explicitly registered Search Indexes and verify vector definitions and cluster configurations

The Couchbase (Vector & NoSQL) MCP Server exposes 7 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Couchbase (Vector & NoSQL) to OpenAI Agents SDK via MCP

Follow these steps to integrate the Couchbase (Vector & NoSQL) MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 7 tools from Couchbase (Vector & NoSQL)

Why Use OpenAI Agents SDK with the Couchbase (Vector & NoSQL) MCP Server

OpenAI Agents SDK provides unique advantages when paired with Couchbase (Vector & NoSQL) through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Couchbase (Vector & NoSQL) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Couchbase (Vector & NoSQL) MCP Server delivers measurable value.

Automated workflows: build agents that query Couchbase (Vector & NoSQL), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Couchbase (Vector & NoSQL), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Couchbase (Vector & NoSQL) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Couchbase (Vector & NoSQL) to resolve tickets, look up records, and update statuses without human intervention

Couchbase (Vector & NoSQL) MCP Tools for OpenAI Agents SDK (7)

These 7 tools become available when you connect Couchbase (Vector & NoSQL) to OpenAI Agents SDK via MCP:

execute_n1ql_query

Provision a highly-available JSON Payload generating generic N1QL constraints

fts_search

Perform structural text-based extraction matching asynchronous Content Trees

get_document

Fetch elaborate internal mapped properties limiting Couchbase KV documents

list_buckets

Identify bounded routing spaces inside the Headless Couchbase DB

list_indexes

Enumerate explicitly attached structured rules exporting active Search Indexes

list_scopes

Retrieve explicit UX logging tracing explicit Scope and Collection Object limits

vector_search

Execute static listing mapping structural KNN Vector similarities via Index

Example Prompts for Couchbase (Vector & NoSQL) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Couchbase (Vector & NoSQL) immediately.

"List all search indexes in my cluster"

"Find the top 3 similar products using this vector: [0.12, -0.5, 0.88]"

"Run N1QL query: 'SELECT name, price FROM `travel-sample` WHERE price < 100 LIMIT 5'"

Troubleshooting Couchbase (Vector & NoSQL) MCP Server with OpenAI Agents SDK

Common issues when connecting Couchbase (Vector & NoSQL) to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Couchbase (Vector & NoSQL) + OpenAI Agents SDK FAQ

Common questions about integrating Couchbase (Vector & NoSQL) MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.