Oracle Database Connector for AI agents.

Q: How does the Oracle Vector DB MCP handle similarity searches?

It uses Oracle's native VECTORDISTANCE functions. You can ask your agent to find similar items using either cosine or Euclidean metrics directly on your vector columns.

Q: Can I run arbitrary SQL — not just vector searches?

Yes. The executesqlquery tool accepts any valid Oracle SQL statement and returns results through ORDS. Add FETCH FIRST N ROWS ONLY to keep payloads manageable. This makes the agent useful for relational queries too, not just vector operations.

7 live capabilities

Run vector similarity searches and manage Oracle 23ai indexes.

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AI Agent

Why people use Oracle Database

Oracle Vector DB for Enterprise RAG and Vector Similarity

This Connector changes the game by letting you keep everything in one place. You can query your production Oracle 23ai database directly from your AI client. You get the power of native vector similarity searches without the headache of managing a second database, giving you a unified source of truth for your AI workflows.

What Vinkius changes

You get a direct line from your AI client to your Oracle 23ai vector store.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

Real-world use case 01

Testing RAG Accuracy

An ML engineer asks the agent to find the 5 most similar documents to a new embedding using `vector_search` to verify their retrieval logic.
Real-world use case 02

Schema Auditing

A data engineer asks the agent to list all tables and describe them to find every column currently using the VECTOR data type.
Real-world use case 03

Performance Tuning

A DBA asks the agent to pull optimizer stats for a specific table using `table_stats` to see why a query is running slowly.

Complete set · 7capabilities

The complete Oracle Database capability set.

These are the exact actions your AI can choose when you ask it to work with Oracle Database.

Capability set01 / 02

01—04

4 capabilities in this set.

Part of 7 available through Oracle Database.

01 Capability
Describe table
Get the full schema for a table, including data types. You can use this to find specific VECTOR columns.
02 Capability
Execute sql query
Run custom SQL queries against your Oracle database via ORDS. Keep your row counts low to ensure the AI stays stable.
03 Capability
Table stats
Get row counts and optimizer statistics for your tables. It's great for planning your capacity and tuning performance.
04 Capability
Get database version
Check the exact Oracle DB runtime version banner. Use this to confirm your instance supports 23ai vector features.

Capability set02 / 02

05—07

3 capabilities in this set.

Part of 7 available through Oracle Database.

05 Capability
List tables
See all the tables available in your current Oracle schema. This helps you quickly identify where your data lives.
06 Capability
Vector search
Execute native VECTOR_DISTANCE queries to find similar neighbors. This works with both cosine and Euclidean metrics.
07 Capability
List vector indexes
See a list of all HNSW and IVF vector indexes. Use this to check your index status across different tables.

Set up in minutes

One URL. Then ask Oracle Database to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Oracle Database from the conversation.

Choose your client

Live preview

Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp

Step 01

Open Connectors

In Claude Web or Claude Desktop, open Settings and choose Connectors.
Step 02

Add the URL

Choose Add custom connector, name it Oracle Database, and paste the URL above.
Step 03

Turn it on in chat

Select +, open Connectors, and enable Oracle Database for the conversation.

ChatGPT · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp

Step 01

Open MCP settings

On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
Step 02

Add the URL

Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Oracle Database URL.
Step 03

Save and start

Save the connection and enable Oracle Database in your conversation. Desktop may ask you to restart once.

Cursor · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "oracle-vector-db": {
      "url": "https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp"
    }
  }
}

Step 01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Step 02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens
Step 03

Save the file

Cursor will automatically detect the new Connector
Step 04

Start using Oracle Database

Open Agent mode in chat and ask: "Using Oracle Database, help me...". 7 tools available

VS Code Copilot · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "oracle-vector-db": {
      "url": "https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp"
    }
  }
}

Step 01

Create MCP config

Create a .vscode/mcp.json file in your project root
Step 02

Add the server config

Paste the JSON configuration above
Step 03

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Step 04

Start using Oracle Database

Ask Copilot: "Using Oracle Database, help me...". 7 tools available

Windsurf · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "oracle-vector-db": {
      "url": "https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp"
    }
  }
}

Step 01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Step 02

Add the server

Paste the JSON configuration above into mcp_config.json
Step 03

Save and reload

Windsurf will detect the new server automatically
Step 04

Start using Oracle Database

Open Cascade and ask: "Using Oracle Database, help me...". 7 tools available

Cline · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "oracle-vector-db": {
      "url": "https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp"
    }
  }
}

Step 01

Open Cline MCP Settings

Click the Connectors icon in the Cline sidebar panel
Step 02

Add remote server

Click "Add Connector" and paste the configuration above
Step 03

Enable the server

Toggle the server switch to ON
Step 04

Start using Oracle Database

Ask Cline: "Using Oracle Database, help me...". 7 tools available

Claude Code · Terminal command

Official guide ↗

Advanced setup

claude mcp add oracle-vector-db --transport http "https://edge.vinkius.com/vk_preview_Bs3fBgLmPqQPV1iPDfqOKsvG2g10fcqpkDZdhwp8/mcp"

Step 01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed
Step 02

Add the Connector

Run the command above in your terminal
Step 03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session
Step 04

Start using Oracle Database

Ask Claude: "Using Oracle Database, show me...". 7 tools are ready

Where the request belongs

Work Oracle Database can move forward.

Built around the request

The ML engineer who needs to test RAG pipelines on production data without leaving their IDE. The DBA who wants to check vector indexes using natural language. The enterprise data team tired of switching between SQL capabilities and AI chat windows.

ML Engineer

Testing embedding queries against real production data to refine RAG accuracy.

Data Engineer

Mapping out vector columns and verifying schema types for new embedding pipelines.

Database Administrator

Checking HNSW index status and optimizer stats without opening a dedicated SQL client.

Build the capability set

Each Connector adds new actions and data without changing how you work.

Browse Connectors

01 6 capabilities

pgvector (Vector Database)

Run vector similarity searches, manage embedding tables, and build AI-powered retrieval pipelines. all directly inside your existing PostgreSQL database.

View Connector

02 7 capabilities

Supabase Vector

Connect your AI to Supabase Vector. Execute pgvector semantic searches, manage embeddings, and run relational database queries directly from your terminal.

View Connector

03 6 capabilities

LanceDB (Serverless Vector DB)

Manage vectorized data via LanceDB. perform similarity searches, create tables, and manage multi-modal embeddings.

View Connector

04 7 capabilities

Couchbase (Vector & NoSQL)

Manage vector search and NoSQL via Couchbase. execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.

View Connector

05 7 capabilities

ClickHouse (Vector Search)

Manage vector embeddings and SQL via ClickHouse. list databases, execute SQL, and perform high-speed vector searches directly from any AI agent.

View Connector

06 6 capabilities

MyScale (SQL Vector Database API)

Manage MyScale vector databases via SQL. execute queries, perform vector searches, and manage indices directly from any AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep Oracle Database connected.

Claude
ChatGPT
Gemini
Cursor
VS Code
Windsurf
ZCode
Cline
Zed
Continue
Kiro
Roo Code
Zencoder
Goose
Void
Augment Code
Amp
Qodo
Tabnine
Pieces
Sourcegraph Cody
JetBrains
Warp
Amazon Q
Antigravity
BoltAI
Raycast
Jan
LM Studio
AnythingLLM
Open WebUI
Msty
Cherry Studio
LibreChat
TypingMind
Chorus
5ire
n8n
LangChain
LlamaIndex
CrewAI
Vercel AI SDK

Before you connect

Questions about Oracle Database.

The practical details behind the request, access and result.

Does the Oracle Vector DB MCP work with my existing Oracle database?

Yes, it works with Oracle Database 23ai. It connects to your existing setup via Oracle ORDS, allowing your AI agent to interact with your current tables and vector columns.

Can I use the Oracle Vector DB MCP for RAG applications?

Absolutely. It's designed to help you build RAG pipelines by letting your agent perform native vector similarity searches and retrieve relevant context from your Oracle data.

Do I need to move my data to a new database to use this?

No, you don't have to move anything. This Connector lets you use your existing Oracle 23ai instance as your vector store, keeping your data centralized and secure.

How does the Oracle Vector DB MCP handle similarity searches?

It uses Oracle's native VECTOR_DISTANCE functions. You can ask your agent to find similar items using either cosine or Euclidean metrics directly on your vector columns.

Can I use this Connector to manage my database indexes?

Yes, you can use it to list and inspect HNSW and IVF vector indexes. This helps you keep track of your AI search infrastructure without leaving your AI client.

Is it safe to run SQL queries through an AI agent?

Yes, the Connector connects via Oracle ORDS. You can run ad-hoc queries for analysis, and the capability includes reminders to limit row counts to keep your AI agent's responses stable.

Does it work with Oracle Autonomous Database?

Yes. Oracle Autonomous Database on OCI has ORDS enabled by default. Use the ORDS URL from your ADB instance (e.g., https://xxxxx.adb.us-ashburn-1.oraclecloudapps.com/ords), your schema name (typically ADMIN), and the admin credentials. The VECTOR type is available on all 23ai-compatible instances.

Can I run arbitrary SQL. not just vector searches?

Yes. The execute_sql_query capability accepts any valid Oracle SQL statement and returns results through ORDS. Add FETCH FIRST N ROWS ONLY to keep payloads manageable. This makes the agent useful for relational queries too, not just vector operations.

Which distance metrics are available for vector search?

Oracle 23ai supports COSINE and EUCLIDEAN (L2) distance metrics natively via VECTOR_DISTANCE. Specify the metric when running a search. cosine is recommended for most text embedding use cases, while L2 works better for image or audio embeddings.

One connection away

Give your agent a direct line to Oracle Database.

Connect Oracle Database once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available

Oracle Vector DB for Enterprise RAG and Vector Similarity

You get a direct line from your AI client to your Oracle 23ai vector store.

Testing RAG Accuracy

Schema Auditing

Performance Tuning

Describe table

Execute sql query

Table stats

Get database version

List tables

Vector search

List vector indexes

Open Connectors

Add the URL

Turn it on in chat

Open MCP settings

Add the URL

Save and start

Open MCP Settings

Add the server config

Save the file

Start using Oracle Database

Create MCP config

Add the server config

Enable Agent mode

Start using Oracle Database

Open MCP Settings

Add the server

Save and reload

Start using Oracle Database

Open Cline MCP Settings

Add remote server

Enable the server

Start using Oracle Database

Install Claude Code

Add the Connector

Verify the connection

Start using Oracle Database

ML Engineer

Data Engineer

Database Administrator

pgvector (Vector Database)

Supabase Vector

LanceDB (Serverless Vector DB)

Couchbase (Vector & NoSQL)

ClickHouse (Vector Search)

MyScale (SQL Vector Database API)

Give your agent a direct line to Oracle Database.