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 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.

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.

Oracle Vector DB MCP Server for AutoGen 7 tools — connect in under 2 minutes

Name: Oracle Vector DB
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 7 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Oracle Vector DB as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

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 autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="oracle_vector_db_agent",
            tools=tools,
            system_message=(
                "You help users with Oracle Vector DB. "
                "7 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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* 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 Oracle Vector DB MCP Server

Bring your Oracle Database 23ai vector capabilities directly into your AI agent workflow. Run VECTOR_DISTANCE similarity searches, inspect table schemas, execute SQL queries, and manage vector indexes — all through natural conversation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Oracle Vector DB tools. Connect 7 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Vector Similarity Search — Execute native Oracle 23ai VECTOR_DISTANCE queries with cosine or Euclidean metrics against any table with VECTOR columns
Schema Inspection — List all tables in your schema and describe column types, spotting VECTOR-enabled columns for embedding storage
SQL Execution — Run arbitrary SQL queries against Oracle via ORDS for ad-hoc analysis and data retrieval
Vector Index Management — List all HNSW and IVF vector indexes instantiated across your tables
Table Statistics — Get row counts and optimizer stats for capacity planning and query performance tuning
Version Check — Verify your Oracle runtime version to confirm 23ai vector feature compatibility

The Oracle Vector DB MCP Server exposes 7 tools through the Vinkius. Connect it to AutoGen 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 Oracle Vector DB to AutoGen via MCP

Follow these steps to integrate the Oracle Vector DB MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 7 tools from Oracle Vector DB automatically

Why Use AutoGen with the Oracle Vector DB MCP Server

AutoGen provides unique advantages when paired with Oracle Vector DB through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Oracle Vector DB tools to solve complex tasks

Role-based architecture lets you assign Oracle Vector DB tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Oracle Vector DB tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Oracle Vector DB tool responses in an isolated environment

Oracle Vector DB + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Oracle Vector DB MCP Server delivers measurable value.

Collaborative analysis: one agent queries Oracle Vector DB while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Oracle Vector DB, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Oracle Vector DB data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Oracle Vector DB responses in a sandboxed execution environment

Oracle Vector DB MCP Tools for AutoGen (7)

These 7 tools become available when you connect Oracle Vector DB to AutoGen via MCP:

describe_table

Describe table columns and explicit data types including VECTORs

execute_sql_query

WARNING: Output payload size is inherently limited, restrict rows fetched (FETCH FIRST 100 ROWS ONLY) to ensure stability. Execute arbitrary SQL query against the Oracle runtime via ORDS

get_database_version

Get exact Oracle DB Runtime version banner

list_tables

List accessible tables in the current Oracle schema

list_vector_indexes

List specialized AI Vector search indexes (HNSW, IVF) instantiated

table_stats

Get table cardinality and optimizer statistics

vector_search

1, -0.4, 0.5]` against a strict `VECTOR` column natively inside Oracle DB, sorting and fetching the nearest neighbors. Execute Vector similarity search via Oracle 23ai native VECTOR_DISTANCE

Example Prompts for Oracle Vector DB in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Oracle Vector DB immediately.

"Show me all tables in my schema that have VECTOR columns."

"Find the 5 most similar documents to this embedding using cosine distance."

"What version of Oracle is running and does it support vectors?"

Troubleshooting Oracle Vector DB MCP Server with AutoGen

Common issues when connecting Oracle Vector DB to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Oracle Vector DB + AutoGen FAQ

Common questions about integrating Oracle Vector DB MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Oracle Vector DB tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.