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InovaflowMCP Server Development

Different customers. Different systems.
Your AI agent needs to reach them all.

We build MCP servers for B2B SaaS companies shipping agentic AI products. Your agents get real-time read and write access to enterprise ERPs, CRMs, databases, and any system with an API. Scoped and delivered in 1-2 weeks.

Why SaaS teams outsource MCP development

01

Enterprise APIs are a different world

SAP's auth flows, NetSuite's SuiteTalk, Dynamics 365 OData — these aren't simple REST endpoints. Each has its own authentication model, data structure, and rate limits. Your AI team shouldn't have to learn all of this.

02

Sandbox access is the hidden blocker

You can't build an MCP server for SAP without a SAP sandbox. Getting one takes weeks and costs thousands. Most teams get stuck before writing a single line of code.

03

Building in-house pulls engineers off your AI

Your team's expertise is in AI — models, prompts, agents, UX. Integration plumbing is a different skillset entirely. Every week on ERP documentation is a week not improving your product.

We've already solved all three. Enterprise partnerships give us sandbox access on day one. We know the APIs inside out. Your team stays on AI — we handle the data layer.


Custom-built MCP servers.
Unlimited tools.

Finance & AP
Invoice matching · PO reconciliation
Retail & Inventory
Stock checks · Reorder automation
Sales & CRM
Pipeline updates · Cross-system sync
AI Agent
finance · ap
MCP Server ready
MCP Tool Calls
System Response
Waiting for tool call...

What's included in every MCP server

Tool Architecture & Design

Custom MCP tools mapped to your agent's needs

Unlimited Read + Write

Full bidirectional access to every connected system

Enterprise Auth

OAuth 2.0, API keys, custom authentication flows

Sandbox Testing

Tested against our enterprise sandbox environments

Full Documentation

Deployment guide, tool reference, and data models

4h Post-Launch Support

Included free. Extended support available.

Delivered in 1-2 weeks · We start building within days

Three steps. Two weeks. Done.

01

Define tools and scope

1-2 days

You tell us what your AI agent needs to do — read invoices, create contacts, query inventory. We map out the MCP tools, data models, and auth requirements. Fixed quote before we start.

02

We build on our sandboxes

1-2 weeks

We develop and test against our own enterprise sandbox environments. No waiting for your customers' systems. Weekly demos so you see progress. Direct Slack access to the engineers building it.

03

Deploy and connect

Same day

Full handover: deployed server, documentation, tool reference. We walk your team through testing against real systems. 4 hours of post-launch support included.

Most AI teams don't know ERPs.
Most ERP experts don't know MCP.

MCP + ERP expertise

Both worlds. One team.

Sandbox access day one

SAP, NetSuite, D365 environments ready.

1-2 week delivery

3-5 active projects max. Senior engineers only.

Every option has trade-offs.

In-house Freelancer MCP agency Inovaflow
Delivery 2-4 weeks (your team knows MCP) 3-5 weeks if available 4-6 weeks 1-2 weeks
MCP knowledge Strong — it's your team Varies widely Likely competent Strong
Enterprise APIs Weak — SAP, NetSuite, D365 are a different world Rarely knows enterprise systems Generic API knowledge, not ERP-specific Battle-tested across major ERPs
Sandbox access Weeks to arrange, costs thousands You provide it You provide it We have our own environments
Your team Pulled off AI product work Managing a contractor Managing a vendor Stays on product
After delivery You maintain everything Gone after invoice Varies — often project-based 4h included + extended available
Cost model Salary + opportunity cost Hourly, variable Project-based, often padded Fixed quote upfront
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We build MCP servers where the data layer is the hard part.

Good fit

  • AI agents that need real-time access to SAP, NetSuite, D365, or Salesforce
  • Teams that need both read and write access to enterprise systems
  • Companies that want fixed scope, fast delivery, and senior engineers
  • Products that need enterprise sandbox environments for development

Not a fit

  • Simple API wrappers that don't require enterprise system knowledge
  • Teams that already have sandbox access and MCP expertise in-house
  • Looking for ongoing managed services or full-time embedded engineers
  • Generic web development or design work

Want to make YOUR product AI-accessible?

+

Your users and internal teams want to build with LLMs. We build MCP servers not just for connecting TO enterprise systems — but for making YOUR SaaS the system AI agents connect to. Let users and internal teams read, write, and act inside your platform through AI, taking your product to the next level.

Tell us about your product →

Everything you need to know
about MCP servers.

What is an MCP server?

MCP (Model Context Protocol) is a standard that allows AI agents and LLM-powered applications to connect to external tools and data sources. An MCP server exposes tools — functions that let the AI read data, create records, update fields, and perform actions in systems like ERPs, CRMs, and databases. Think of it as the bridge between your AI and the real world.

How long does it take to build an MCP server?

We typically deliver in 1-2 weeks, depending on the number of systems and tools needed. Simple single-system servers can be faster. We scope in 1-2 days and start building immediately.

Which enterprise systems can you build MCP servers for?

SAP S/4HANA, Microsoft Dynamics 365, Oracle NetSuite, Salesforce, HubSpot, Snowflake, BigQuery, PostgreSQL, MongoDB, and any system with a REST, GraphQL, or SOAP API. We maintain sandbox environments for major ERPs through our partnership programs.

Do I need to provide sandbox access?

No. We maintain our own enterprise sandbox environments through vendor partnership programs. This is one of the biggest blockers for teams building MCP servers in-house — we've already solved it.

Can the MCP server both read and write data?

Yes. Every MCP server we build includes unlimited tools for full bidirectional access. Your AI agent can query data, create new records, update existing ones, and trigger actions in connected systems.

What's the difference between an MCP server and a regular API integration?

A regular API integration is point-to-point — you connect system A to system B with fixed logic. An MCP server is agent-driven — it exposes tools that an AI agent can choose to use dynamically based on context. The AI decides what to call, when, and with what parameters. It's fundamentally more flexible for AI applications.

How much does an MCP server cost?

Pricing depends on the number of connected systems and tools required. We provide a fixed quote after a scope call — usually within 1-2 days. Book a scope call and we'll give you a timeline and cost before the call ends.

Can you build an MCP server for our SaaS product?

Yes. We don't just connect AI agents to enterprise systems — we also build MCP servers that make YOUR product AI-accessible. Your users and internal teams can then build with LLMs against your platform, taking your product to the next level. Same engineering team, same quality.

Let's scope your MCP server.

Tell us what systems your AI needs to access. We'll come back with a tool design, timeline, and fixed quote — usually within 48 hours.

Book a Scoping Call Book a Call

or email us directly — hello@inovaflow.io