How to Use the Ensembl MCP in Vercel AI SDK

Q: How do I connect the Ensembl MCP Server to my Vercel AI SDK project?

Install @ai-sdk/mcp to register this MCP Server and call createMCPClient using the Vinkius HTTP transport URL. Pass the tools directly to streamText to let your agent call endpoints like getsequenceid during live chat.

Q: Can my Vercel AI SDK agent compare Ensembl gene structures?

Yes, your agent can call gethomology to find evolutionary relationships between species. It can then fetch the exact genomic coordinates of those homologous genes using getlookupid to map out structural differences.

Fetch raw genomic sequences and variant data directly into your Vercel AI SDK stream without blocking UI renders.

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Connect Ensembl MCP to Vercel AI SDK

Create your Vinkius account to connect Ensembl to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Ensembl with Vercel AI SDK

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Stream variant predictions to Vercel AI SDK frontends

`get_vep_id` pulls variant consequence predictions directly into your Vercel AI SDK application. When your agent evaluates a genomic variant, the raw consequence data streams right into the React UI without waiting for a massive payload to finish parsing. For batch operations, `get_vep_bulk` handles multiple positions in a single call. This setup lets your client process long variant lists on Edge Functions and render them piece-by-piece to keep the interface responsive.

Stream genomic sequences directly with this MCP Server

`get_sequence_id` fetches specific nucleotide or amino acid sequences based on stable Ensembl identifiers. Your Vercel AI SDK application streams this sequence data character-by-character into the browser, letting researchers see the DNA strand populate without page freezes. You can also call `get_sequence_region` to pull specific chromosomal coordinates. This avoids loading whole chromosomes into memory, allowing edge runtimes to process the data fast and keep cold starts low.

Map gene symbols during live chat sessions

`get_xrefs_symbol` resolves common gene names to their official Ensembl database records in real-time. This tool lets your Vercel AI SDK chat agent instantly translate user queries like BRCA1 into precise identifiers. The client then feeds those IDs into `get_lookup_id` to verify species and database origins. Because the SDK handles async tool outputs natively, your UI updates the gene metadata card the moment the Ensembl database responds.

Setup guide

Set up Ensembl MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Ensembl tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Ensembl transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ensembl. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Ensembl MCP in Vercel AI SDK

Install `@ai-sdk/mcp` to register this MCP Server and call `createMCPClient` using the Vinkius HTTP transport URL. Pass the tools directly to `streamText` to let your agent call endpoints like `get_sequence_id` during live chat.

Yes, because this setup is fully compatible with Edge runtimes. Your agent can run `get_vep_bulk` inside an Edge Function to fetch variant predictions without hitting the 15-second execution limits of standard serverless platforms.

The SDK executes tool calls sequentially or in parallel depending on your agent configuration. If you run bulk operations like `get_lookup_bulk`, you reduce total roundtrips to stay well within the Ensembl REST API rate limits.

Yes, your agent can call `get_homology` to find evolutionary relationships between species. It can then fetch the exact genomic coordinates of those homologous genes using `get_lookup_id` to map out structural differences.

Your raw nucleotide and peptide data passes through Vinkius's ephemeral sandboxes directly to your Vercel deployment. No genomic sequences or variant coordinates are cached or stored on Vinkius servers.

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