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.
README
Couchbase MCP Server
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.inventorydata. - 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-samplebucket loaded with theinventoryscope. - 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
inventoryscope. - SQL++ queries should run in a scoped query context, so the
FROMclause 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=falsefor 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
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