couchbase-mcp-server

couchbase-mcp-server

Enables natural-language AI agents to query and manage Couchbase databases via the Model Context Protocol, allowing users to ask plain-English questions about travel data and get SQL++-backed answers.

Category
Visit Server

README

Couchbase MCP Server

Validate Live Demo Site Python License: MIT

A production-shaped demo that connects a natural-language AI agent to Couchbase through the Model Context Protocol (MCP). It uses the OpenAI Agents SDK as the agent runtime, a stdio MCP server as the tool bridge, Couchbase travel-sample as the data source, and a Nebius-hosted OpenAI-compatible model as the LLM backend.

Live project site: https://tirth1263.github.io/couchbase-mcp-server/

Why This Project Exists

LLMs are good at understanding intent, but they need trustworthy tools to answer questions grounded in private or operational data. MCP gives those tools a standard shape. This repository demonstrates that pattern end to end:

  • A user asks a plain-English travel question.
  • The OpenAI Agents SDK agent decides whether it needs database context.
  • The agent calls a Couchbase MCP tool over stdio.
  • The MCP server executes scoped SQL++ against the travel-sample.inventory data.
  • The agent turns the database result into a clear recommendation or answer.

Example questions:

  • "List out the top 5 hotels by the highest aggregate rating."
  • "Recommend me a flight and hotel from New York to San Francisco."
  • "Which airports are near San Francisco and what routes connect to them?"

Architecture

flowchart LR
    U["User question"] --> N["main.ipynb / CLI demo"]
    N --> A["OpenAI Agents SDK agent"]
    A --> M["MCPServerStdio client"]
    M <--> S["Couchbase MCP server"]
    S --> C["Couchbase travel-sample bucket"]
    A --> L["Nebius OpenAI-compatible LLM"]
    C --> S --> M --> A --> R["Natural-language answer"]

What Is Included

  • src/couchbase_mcp_server/mcp_server.py - the stdio MCP server.
  • src/couchbase_mcp_server/couchbase_client.py - Couchbase SDK wrapper and JSON serialization.
  • src/couchbase_mcp_server/demo_agent.py - command-line OpenAI Agents SDK demo.
  • main.ipynb - Jupyter notebook version of the demo.
  • .env.example - environment variables for Couchbase and Nebius.
  • docs/ - static GitHub Pages website.
  • tests/ - focused safety tests for SQL++ mutation detection.

MCP Tools Exposed

Tool Purpose
get_connection_summary Shows the configured bucket, scope, host, and read/write mode without exposing secrets.
get_scopes_and_collections Lists scopes and collections in the configured Couchbase bucket.
run_sql_plus_plus_query Runs SQL++ in the configured bucket/scope query context.
get_document_by_id Fetches a document from a named collection in the inventory scope.
get_sample_queries Returns useful SQL++ examples for the travel-sample inventory data.

By default, run_sql_plus_plus_query blocks mutations such as INSERT, UPDATE, DELETE, MERGE, CREATE, DROP, and ALTER. Set COUCHBASE_ALLOW_MUTATIONS=true only when you intentionally want write-capable tools.

Prerequisites

  • Python 3.11 or newer. Python 3.12 is recommended.
  • Jupyter Notebook or JupyterLab for main.ipynb.
  • A running Couchbase Server or Couchbase Capella instance.
  • The travel-sample bucket loaded with the inventory scope.
  • A Nebius API key for an OpenAI-compatible chat model endpoint.

Quick Start

Clone and install:

git clone https://github.com/tirth1263/couchbase-mcp-server.git
cd couchbase-mcp-server
python -m venv .venv
source .venv/bin/activate
pip install -e ".[notebook]"

On Windows PowerShell:

git clone https://github.com/tirth1263/couchbase-mcp-server.git
cd couchbase-mcp-server
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -e ".[notebook]"

Create your environment file:

cp .env.example .env

Then edit .env:

COUCHBASE_HOST=couchbases://your-capella-endpoint
COUCHBASE_BUCKET_NAME=travel-sample
COUCHBASE_SCOPE_NAME=inventory
COUCHBASE_USERNAME=your_couchbase_username
COUCHBASE_PASSWORD=your_couchbase_password
NEBIUS_API_KEY=your_nebius_api_key
NEBIUS_BASE_URL=https://api.studio.nebius.ai/v1/
NEBIUS_MODEL=meta-llama/Meta-Llama-3.1-8B-Instruct

Run the MCP Server

You can start the MCP server directly:

python -m couchbase_mcp_server.mcp_server --env-file .env

The server uses stdio, so it is usually launched by an MCP client rather than run interactively. Logs are written to stderr so stdout stays reserved for MCP messages.

Run the Agent Demo

Notebook:

jupyter lab main.ipynb

CLI:

couchbase-agent-demo "List the top 5 hotels by aggregate rating."

Or:

python -m couchbase_mcp_server.demo_agent \
  --env-file .env \
  "Recommend a flight and hotel from New York to San Francisco."

Agent Instructions

The demo agent is intentionally explicit about Couchbase structure:

  • A Couchbase cluster contains buckets.
  • A bucket contains scopes.
  • A scope contains collections.
  • Collections contain JSON documents.
  • The target demo data lives in the inventory scope.
  • SQL++ queries should run in a scoped query context, so the FROM clause can use collection names like `hotel` rather than fully qualified paths.
  • All identifiers should be wrapped in backticks.

That last point matters because SQL++ collection and field names can collide with keywords or include characters that need quoting.

Website

The public website is served from docs/ using GitHub Pages:

https://tirth1263.github.io/couchbase-mcp-server/

The site is a static deployment artifact, so it can also be hosted on Netlify, Vercel, Cloudflare Pages, or any static web server without a build step.

Development

Run validation:

python scripts/validate_project.py
python -m compileall src
pytest

Format and lint if you install the dev extras:

pip install -e ".[dev,notebook]"
ruff check .
ruff format .

Security Notes

  • Do not commit .env; it is intentionally ignored.
  • Keep COUCHBASE_ALLOW_MUTATIONS=false for demos, workshops, and public examples.
  • Use a least-privilege Couchbase user with access only to the demo bucket/scope.
  • Prefer read-only database credentials unless you are intentionally demonstrating write tools.
  • Treat LLM-generated SQL++ as untrusted input and keep server-side guardrails in place.

References

  • OpenAI Agents SDK: https://openai.github.io/openai-agents-python/
  • Agents SDK MCP integration: https://openai.github.io/openai-agents-python/mcp/
  • Model Context Protocol: https://modelcontextprotocol.io/
  • Couchbase Python SDK: https://docs.couchbase.com/python-sdk/current/hello-world/start-using-sdk.html
  • Couchbase travel-sample: https://docs.couchbase.com/server/current/getting-started/do-a-quick-install.html#install-sample-buckets

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured