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Vercel AI SDKSDK
RSS Feed Parser MCP Server

Bring Rss
to Vercel AI SDK

Learn how to connect RSS Feed Parser to Vercel AI SDK and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

MCP Inspector GDPR Free for Subscribers
Parse Rss Feed

Compatible with every major AI agent and IDE

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ChatGPTChatGPT
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GeminiGemini
WindsurfWindsurf
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JetBrainsJetBrains
VercelVercel
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RSS Feed Parser

What is the RSS Feed Parser MCP Server?

Your content marketing agent needs to monitor 20 competitor blogs, 5 industry news feeds, and 3 podcast channels. Without a parser, it scrapes HTML — inconsistent, slow, and full of noise.

RSS and Atom feeds are the web's native content API. This MCP parses them into clean JSON objects with titles, links, publication dates, authors, categories, and full content — ready for summarization, curation, or automated distribution.

The Superpowers

  • RSS 2.0 + Atom: Both formats parsed identically into a unified JSON structure.
  • Full Content: Extracts title, link, date, author, categories, enclosures (podcasts), and content/summary.
  • No Scraping: Clean, structured data from the feed XML — no HTML parsing, no DOM traversal.
  • Podcast Ready: Enclosure extraction for audio/video URLs, durations, and file sizes.

Built-in capabilities (1)

parse_rss_feed

Pass the raw XML string and receive a structured JSON with feed metadata and up to 20 items. This is essential for content marketing agents monitoring blogs, news aggregators, and podcast feeds. Never try to parse XML manually — use this engine for deterministic extraction. Parses RSS 2.0 and Atom feed XML into structured JSON objects. Extracts title, description, items with links, dates, categories, and content snippets

Why Vercel AI SDK?

The Vercel AI SDK gives every RSS Feed Parser tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 1 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 RSS Feed Parser integration everywhere

  • Built-in streaming UI primitives let you display RSS Feed Parser 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

See it in action

RSS Feed Parser in Vercel AI SDK

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

RSS Feed Parser and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect RSS Feed Parser 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.

4,000+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself4,000+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for RSS Feed Parser in Vercel AI SDK

The RSS Feed Parser 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 1 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.

RSS Feed Parser
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

The Vinkius Advantage

How Vinkius secures RSS Feed Parser for Vercel AI SDK

Every tool call from Vercel AI SDK to the RSS Feed Parser MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

Does it work with podcast feeds?

Yes. Podcast RSS feeds include enclosure elements with audio/video URLs, MIME types, and file sizes. The parser extracts all of them.

02

Can it handle both RSS 2.0 and Atom?

Yes. Both formats are auto-detected and parsed into the same unified JSON structure. Your agent doesn't need to know which format the source uses.

03

Does it fetch the feed URL or do I pass the XML?

Pass the feed URL and the engine fetches + parses in one step. No manual XML handling needed.

04

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.

05

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.

06

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.

07

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

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