How to Use the PMC Open Access (PubMed Central) MCP in Vercel AI SDK
Stream PubMed Central research metadata directly into your Next.js frontend using the Vercel AI SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect PMC Open Access (PubMed Central) MCP to Vercel AI SDK
Create your Vinkius account to connect PMC Open Access (PubMed Central) to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Gemini
Key Capabilities
Vercel AI SDK citations
The `convert_ids` tool maps DOIs, PMIDs, and PMCIDs instantly so your Vercel AI SDK app can resolve references on the fly. You pass a manuscript ID. The server fires back the exact crosswalk matches as JSON. Because you use `export_citation` with this framework, the resulting BibTeX or RIS strings stream straight into your React components. Users watch the bibliography build itself in real time instead of staring at a blank screen.
Stream open-access metadata
The `oa_discover` tool pulls downloadable resource links from the PMC Open Access Subset. Your agent queries the subset, grabs the exact URLs for full-text archives, and pushes them to the client. Pair this with `oai_get_record` to fetch specific OAI XML records. The payload drops right into your Vue or Svelte state management. You skip the backend polling loop completely.
Query PMC MCP Server records
The `oai_list_identifiers` tool fetches batches of OAI identifiers based on your specific metadata prefix. You get a raw list of what is available in the repository before committing to heavy downloads. Your MCP client then calls `oai_list_metadata_formats` to verify schema compatibility. It is a fast, predictable way to build search interfaces for medical researchers.
Set up PMC Open Access (PubMed Central) MCP in Vercel AI SDK
Prerequisites
- Node.js 18+ and a TypeScript project
-
ai+@modelcontextprotocol/sdkpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install ai @modelcontextprotocol/sdkplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Create the Streamable HTTP transport
Use
StreamableHTTPClientTransportwith 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 PMC Open Access (PubMed Central) tools. Pass them directly togenerateText()orstreamText()— 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.
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 PMC Open Access (PubMed Central) transactions",
});
console.log(text);
await mcpClient.close();Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PMC (PubMed Central). 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 PMC Open Access (PubMed Central) MCP in Vercel AI SDK
Use it with your favorite AI tools
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