Oracle Vector DB MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Oracle Vector DB through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Oracle Vector DB, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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.
The Vercel AI SDK gives every Oracle Vector DB tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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 Vercel AI 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 Oracle Vector DB to Vercel AI SDK via MCP
Follow these steps to integrate the Oracle Vector DB MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 7 tools from Oracle Vector DB and passes them to the LLM
Why Use Vercel AI SDK with the Oracle Vector DB MCP Server
Vercel AI SDK provides unique advantages when paired with Oracle Vector DB through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Oracle Vector DB integration everywhere
Built-in streaming UI primitives let you display Oracle Vector DB tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Oracle Vector DB + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Oracle Vector DB MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Oracle Vector DB in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Oracle Vector DB tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Oracle Vector DB capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Oracle Vector DB through natural language queries
Oracle Vector DB MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Oracle Vector DB to Vercel AI SDK 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 Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK 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 Vercel AI SDK
Common issues when connecting Oracle Vector DB to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpOracle Vector DB + Vercel AI SDK FAQ
Common questions about integrating Oracle Vector DB MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Oracle Vector DB with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Oracle Vector DB to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.