Parseur MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Parseur through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
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 Parseur, 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 Parseur MCP Server
Bring Parseur Document Extraction arrays directly into your AI workflows. By explicitly mapping into powerful OCR and templating engines, your agent can push unstructured PDFs or bulk emails into remote routing limits, parsing exact text fields securely. Extract fields, examine documents, list defined parse-templates, and retry pipelines without manual intervention.
The Vercel AI SDK gives every Parseur tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the 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
- Mailboxes & Templates — Examine specifically bound mailboxes tracking which explicit templates dictate data extraction limits mapped natively
- Document Navigation — Extract properties showing precisely which unstructured strings were identified inside uploaded payloads checking
status: parsedcorrectly - Payload Uploading — Instruct the node limits mapping
upload_documentgenerating raw payloads routing straight into the engine for OCR logic - Job Management — Discover disconnected states mitigating failed validations by pushing
retry_documentinstantly forcing physical pipeline resets
The Parseur MCP Server exposes 10 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 Parseur to Vercel AI SDK via MCP
Follow these steps to integrate the Parseur 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 10 tools from Parseur and passes them to the LLM
Why Use Vercel AI SDK with the Parseur MCP Server
Vercel AI SDK provides unique advantages when paired with Parseur 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 Parseur integration everywhere
Built-in streaming UI primitives let you display Parseur 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
Parseur + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Parseur MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Parseur in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Parseur tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Parseur capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Parseur through natural language queries
Parseur MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Parseur to Vercel AI SDK via MCP:
create_mailbox
The type determines the parsing engine (e.g., "pdf", "email", "attachment"). Once created, you can configure templates and forward documents to the mailbox for automatic extraction. Create a new Parseur mailbox for document parsing
create_template
Pass the template name and a JSON config string defining field mappings. Parseur will use this template to extract structured data from matching documents. Create a new extraction template for a Parseur mailbox
get_document_data
Fields depend on the template configuration (e.g., invoice_number, total_amount, line_items). Only works for documents with status "processed". Retrieve the fully extracted JSON data from a parsed document
get_document_details
Does not include the parsed data itself — use get_document_data for that. Get metadata of a single parsed document
get_mailbox
Use this to verify mailbox setup before sending documents. Get detailed configuration of a specific Parseur mailbox
list_documents
Each entry includes document ID, status (processed, failed, pending), and metadata like sender and received date. List all parsed documents inside a Parseur mailbox
list_mailboxes
Each mailbox represents a parsing pipeline for a specific document type (invoices, receipts, emails). Use the returned mailbox IDs for subsequent operations like listing documents or uploading files. List all Parseur parsing mailboxes
list_templates
Templates define the extraction rules (field names, locations, regex patterns) used to pull structured data from incoming documents. List available extraction templates for a Parseur mailbox
retry_document
Useful after fixing template rules or when the original parse failed due to a transient error. The document will be matched against the latest template rules. Retry parsing a failed or errored Parseur document
upload_document
eml) to the specified mailbox for automatic parsing. The document enters the processing queue and will be parsed according to the mailbox template. Returns the new document ID for tracking. Upload a document URL to a Parseur mailbox for parsing
Example Prompts for Parseur in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Parseur immediately.
"Check my Parseur mailboxes to find the specific bounding IDs."
"Get the data schema parsed tightly inside document doc_987."
"Upload this snippet of parsed text directly into Mailbox xyz12 for OCR processing."
Troubleshooting Parseur MCP Server with Vercel AI SDK
Common issues when connecting Parseur to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpParseur + Vercel AI SDK FAQ
Common questions about integrating Parseur 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 Parseur 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 Parseur to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.