Spendesk MCP Server for Mastra AI 9 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Spendesk through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"spendesk": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Spendesk Agent",
instructions:
"You help users interact with Spendesk " +
"using 9 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Spendesk?"
);
console.log(result.text);
}
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 Spendesk MCP Server
Bring your Spendesk financial operations natively into your AI workspace. Eliminate constant tab switching to check the finance dashboard. You can now use conversational prompts to audit real-time company expenses, verify specific payment IDs, and inspect active supplier invoices while writing your integration code or managing operational scripts.
Mastra's agent abstraction provides a clean separation between LLM logic and Spendesk tool infrastructure. Connect 9 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
What you can do
- Track Cash Flow — Monitor organizational outflows by executing
list_payments. Need deep details on a specific transaction? Pull exactly what happened usingget_payment_details - Audit Invoices & Expenses — Keep track of pending vendor bills via
list_invoicesand review employee out-of-pocket reimbursements triggeringlist_expense_claims - Supplier Management — Check your registered vendor matrix using
list_suppliersand pull contact or payment history directly callingget_supplier_details - Control Limits — Actively supervise remaining budget allocations calling
list_budgetsand watch the assigned corporate limits on issued plastic/virtual vialist_cards
The Spendesk MCP Server exposes 9 tools through the Vinkius. Connect it to Mastra AI 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 Spendesk to Mastra AI via MCP
Follow these steps to integrate the Spendesk MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 9 tools from Spendesk via MCP
Why Use Mastra AI with the Spendesk MCP Server
Mastra AI provides unique advantages when paired with Spendesk through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Spendesk without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Spendesk tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Spendesk + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Spendesk MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Spendesk, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Spendesk as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Spendesk on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Spendesk tools alongside other MCP servers
Spendesk MCP Tools for Mastra AI (9)
These 9 tools become available when you connect Spendesk to Mastra AI via MCP:
get_payment_details
Get detailed information about a specific payment
get_supplier_details
Get detailed information about a specific supplier
list_budgets
List all budgets and their spending status
list_cards
List all virtual and physical cards issued
list_expense_claims
List all employee expense claims and reimbursement requests
list_invoices
List all invoices pending or processed
list_members
List all team members with Spendesk access
list_payments
List all payments in the Spendesk account
list_suppliers
List all registered suppliers
Example Prompts for Spendesk in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Spendesk immediately.
"Review Spendesk and show me all recent payments hitting our account."
"Bring a quick summary containing our currently monitored budgets to check for remaining allocated thresholds."
"Let's check our member list in Spendesk to see who holds what permission roles currently."
Troubleshooting Spendesk MCP Server with Mastra AI
Common issues when connecting Spendesk to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpSpendesk + Mastra AI FAQ
Common questions about integrating Spendesk MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Spendesk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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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 Spendesk to Mastra AI
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.