A good API is not just a technical endpoint. It is a controlled way for your website, software, partners and AI tools to ask for the right thing, get a predictable answer, and leave a useful audit trail behind.
ShipMyCar proof point
We built the API and MCP connector behind AI-assisted vehicle quotes.
ShipMyCar needed more than a standard contact form. The platform now has a structured quote API and a public MCP connector so supported AI assistants can collect route, vehicle and contact details, check what is missing, generate pricing through the existing quote engine, and send the customer back to ShipMyCar to continue.
A public quote API that accepts structured vehicle transport details and returns usable pricing.
An MCP connector that lets AI assistants collect missing details before generating a quote.
Guardrails around route support, required services, rate limits, confirmation and continuation links.
A clean hand-off from an AI conversation into the ShipMyCar website so the customer can continue.
What This Means For Your Business
If your team copies the same data between a website, spreadsheet, CRM, accounts package and inbox, there is probably an API or MCP opportunity. We can create the controlled layer that lets those systems talk without making staff work around brittle exports.
For an AI workflow, the important question is not "can we connect AI?" It is "which actions should an assistant be allowed to perform, what information must be checked first, and where should the human hand-off happen?" That is where MCP server development becomes useful.
How We Build It
Shape the API contract
We define the request and response clearly first: what data is required, what can be optional, what errors look like, and what external systems need to trust.
Expose the right AI tools
For MCP, we do not give an assistant unlimited access. We create narrow tools with plain-English descriptions, validation and safe responses.
Add the guardrails
Authentication, rate limits, audit logs, environment switches and confirmation steps keep public automation from becoming a risky back door.
Connect the workflow
The useful part is the hand-off: CRM records, quote links, accounts data, dashboards or team notifications that fit how the business already works.
Useful API and MCP Projects
Partner APIs
Let trusted partners submit jobs, request quotes, check availability or create records safely.
CRM and Xero bridges
Move customer, invoice, quote and payment data without manual retyping.
AI quote tools
Let assistants collect missing details and prepare structured requests for your systems.
Common Questions
What is MCP development?
MCP development means building a Model Context Protocol server so an AI assistant can safely use your business tools, such as quote engines, CRMs, booking systems, stock data, accounts software or internal knowledge.
Do I need an MCP server or a normal API?
Many businesses need both. A normal API gives websites, partners and internal tools a reliable way to exchange data. An MCP server makes selected actions available to AI assistants with clearer instructions, guardrails and user confirmation steps.
Can you connect this to Xero, CRM or quoting software?
Yes. We build APIs and connectors around real workflows: quote creation, customer records, CRM updates, payment links, Xero draft invoices, document checks and follow-up tasks.
Is it secure to expose business tools to AI?
It can be, if the connector is designed properly. We use scoped tools, validation, rate limits, audit logs, explicit confirmation for sensitive actions and a clear split between public lead-generation flows and private business systems.
Give Your Systems A Proper Interface
Tell us which systems you use, where staff are retyping data, and whether the connector is for your website, partners, internal team or AI assistants. We will map the smallest useful API or MCP build.
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