Bring Museum Records
to Vercel AI SDK
Learn how to connect Smithsonian Open Access to Vercel AI SDK and start using 3 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Smithsonian Open Access MCP Server?
Connect to the Smithsonian Open Access repository and bring millions of museum records, scientific data, and historical artifacts directly into your AI workspace. This server provides programmatic access to the Smithsonian's Enterprise Digital Asset Network (EDAN).
What you can do
- Global Search — Query millions of records across all Smithsonian units using the
search_recordstool to find images, specimens, and artifacts. - Detailed Metadata — Use
get_contentto retrieve comprehensive descriptions, provenance, and digital asset links for specific museum objects. - Categorized Discovery — Narrow your research to specific fields like art, history, or science using the
search_categorytool for more precise results. - Research & Education — Instantly pull primary source data for academic research, educational content, or creative projects.
How it works
- Subscribe to this server
- Enter your Smithsonian API Key
- Start exploring the world's largest museum, education, and research complex through Claude, Cursor, or any MCP client
Who is this for?
- Researchers & Academics — quickly gather metadata and primary source information for scholarly work
- Educators — find high-quality museum records and images to enhance learning materials
- Developers & Creatives — integrate authentic historical and scientific data into applications and digital experiences
Built-in capabilities (3)
Retrieve a specific museum record by its unique identifier
Search within specific categories or units
Search for museum records across all Smithsonian units
Why Vercel AI SDK?
The Vercel AI SDK gives every Smithsonian Open Access tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 3 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
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 Smithsonian Open Access integration everywhere
- —
Built-in streaming UI primitives let you display Smithsonian Open Access 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
Smithsonian Open Access in Vercel AI SDK
Smithsonian Open Access and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Smithsonian Open Access to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Smithsonian Open Access in Vercel AI SDK
The Smithsonian Open Access 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. All 3 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Smithsonian Open Access for Vercel AI SDK
Every tool call from Vercel AI SDK to the Smithsonian Open Access MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I search for specific historical figures across all Smithsonian museums?
Yes! Use the search_records tool with your query (e.g., 'Abraham Lincoln'). It will return matching records, images, and artifacts from across all Smithsonian units.
How do I get the full metadata for a specific museum object?
Use the get_content tool with the unique identifier (ID) of the record. This will fetch detailed metadata, including descriptions, dates, and media links.
Is it possible to limit my search to just art or science categories?
Yes, the search_category tool allows you to specify a category (like 'art', 'history', or 'science') along with your search query to get more targeted results.
How does the Vercel AI SDK connect to MCP servers?
Import 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?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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