Production shouldn’t be the first real system your MCP server meets.
We prove it works on ours first.
Done-for-you, end-to-end validation of your ERP and CRM MCP servers against real SAP, NetSuite, Oracle, Dynamics, Coupa, Salesforce and HubSpot environments. Your connector, our sandboxes, our engineers, our test protocol — and a report of what broke, why, and how to fix it.
The code was the easy part.
Proving it is not.
The model wrote a clean server: auth, paging, tool schemas, all of it. What it could not do is check its own assumptions against a real S/4HANA or NetSuite, because there is no signup form for one. So the server ships, and the first real system it ever runs against belongs to a customer.
Some teams get access through a partner program or a friendly customer. Then the roadmap takes priority. The write paths get a smoke test, the edge cases get a TODO, and the production incident gets a post-mortem.
Even with access, an empty tenant proves the API contract and little else. Real systems carry years of configuration: approval workflows, mandatory custom fields, scripts that fire on save, roles that hide data without an error. Each of those is a failure type of its own, and it only shows up when the connector runs against a production-like setup. Agents add failures of their own on top: picking the wrong tool, guessing a field, retrying a write that already went through.
You keep building. We do the proving. Background: Why testing is now the hard part of enterprise integrations.
Your connector. Our environment.
Our engineers run it.
We do not rebuild your MCP server and we do not need access to any of your customers’ systems. We take what you built, run every tool against a real, configured system, and tell you what happened inside it.
The MCP server
Written by your team or generated with Claude. Send us the server, the tool list, and what a pass looks like. We run it, we do not rewrite it.
The sandboxes, the engineers, the protocol
Real S/4HANA, NetSuite, Oracle Fusion, Dynamics 365, Coupa, Salesforce, HubSpot and more, configured like a customer would run them. Operated by people who build these connectors for a living.
What broke, why, and the fix
Every tool, pass or fail, with evidence from inside the system. Findings ranked by severity, each with a concrete fix. One retest included.
Six things a passing test suite cannot tell you.
A unit test proves your code handles the response you imagined. Our protocol is the list of everything real systems have actually done to us — the same checks we run on every connector we ship ourselves, plus the ones only agents need.
Auth under real conditions
- Token refresh over long sessions, expiry mid-batch
- Parallel connections and session limits
- Every auth method the platform exposes, not just the one in the README
Reads on real data
- Custom fields come back, not just the standard object
- Paging survives real volumes
- Permission gaps that hide data silently, without an error
Writes and their side effects
- The intended record and nothing else
- Chains in the right order: find, check, then commit
- Which workflows and scripts fire when the write goes through
Failure behavior
- Real error shapes, HTML where JSON was promised
- Timeouts, rate limits as enforced, a batch that dies at row 48
- What the agent is told when it goes wrong
Agent behavior
- Does the description lead the model to the right tool?
- Are schemas tight enough that it cannot invent a field?
- Confirmation gates on destructive writes, no double post on retry
Configuration sensitivity
- Which assumptions are really per-instance settings
- What breaks at the next customer whose admin set it up differently
- Which reads should happen before any write
The findings that never show up in a unit test.
NetSuite
create_invoice
SAP S/4HANA
post_supplier_invoice
NetSuite
create_item
Salesforce
log_activity
The systems we validate against.
Production-like environments, not empty sandboxes. Each one is configured the way a customer would run it — approval workflows, mandatory fields, roles and permissions, master-data dependencies — so the failures that only appear on a real setup appear here first.
SAP S/4HANA
Invoices, purchase orders, vendors, stock
SAP ECC
The on-prem systems nobody has migrated yet
SAP Business One
SMB finance, sales and inventory
SAP SuccessFactors
People, org data, time off
SAP Ariba
Sourcing, contracts, supplier data
Oracle NetSuite
Bills, records, saved searches
Oracle Fusion
ERP and HCM cloud modules
Dynamics 365 F&O
Finance, supply chain, manufacturing
Dynamics 365 BC
Business Central sales, stock and ledger
Salesforce
Accounts, opportunities, custom objects
HubSpot
Deals, contacts, tickets
Workday
People, absence, payroll
Coupa
Spend, invoices, suppliers
Rossum
Document capture and extraction
Xero
Invoices, contacts, bank feeds
QuickBooks
Invoices, payments, ledger
ServiceNow
Tickets, incidents, CMDB
Jira
Issues, projects, workflows
Snowflake
Reads for context and reporting
BigQuery
Analytics reads and exports
…and anything else with an API. If your target system is not here, ask — the list grows week by week.
Do you have a connector, or do you need one?
Bring your connector when…
You already have an MCP server, written by your team or generated with Claude, and what you lack is a real system to prove it on. We run it, we do not rewrite it, and what you get back is evidence and a fix list.
That is this page.
Ask us to build it when…
There is no connector yet, or the one you have needs more than fixes. We design the tool surface, build it in your repo, and validate it in these same environments before handover.
From “it works on the mock” to proven.
Send us the server
The MCP server or connector, its tool list, and what a pass looks like for each. If you have specific agent tasks in mind, we test those too. About two hours of your time, most of it on one call.
We seed, then we run
We provision the target scope in our sandbox, seed synthetic data for your tool surface (if missing), and run every tool through the protocol: reads, writes, failures, and the agent-behavior checks. Every call is captured with what it did inside the system.
You get the report, then a retest
Coverage matrix, severity-ranked findings with fixes, and a walkthrough with the engineer who ran it. Fix what matters, send it back, and we run it again.
Four ways to find out whether it works.
| Your team on a vendor dev sandbox | Mocks and code review | Wait for the customer’s sandbox | Inovaflow | |
|---|---|---|---|---|
| Time to first real result | Weeks to get access, if at all | Same day — against your own assumptions | After the deal closes, under a deadline | Days — the environments already run |
| Configured like a real customer | Near-empty, vanilla setup | Whatever you mocked | Yes, and you learn it in production | Seeded with realistic data and rules |
| Write paths tested | Risky on a shared tenant | Not really | On their data, with their auditors watching | Fully, with checks inside the system |
| Agent-specific checks | Only if someone thinks of them | No | No | Tool choice, schema guessing, double writes |
| Who reads the results | Your engineers | Your engineers | Their architects, and they will not be happy | A report your sales team can hand to security review |
| Cost model | Weeks of engineer time, plus getting the access | Cheap — and the results show it | A stalled deal | Fixed quote per server and system |
Why the bottleneck moved from writing to proving: Connector validation.
We are selective. You should be too.
Good fit
- Agentic B2B SaaS teams with an MCP server or connector already built, often AI-generated
- Integration platforms that need every ERP and CRM connector proven before it goes GA
- Teams that have a sandbox but not the time to test writes, edge cases and agent behavior
- Anyone whose next enterprise buyer will ask “show us this on our SAP”
Not a fit
- No connector yet — see MCP connector development
- Prototypes and demos that will never reach a customer’s system
- Load, performance or penetration testing
- Testing against production systems, or with real customer data
We test them the way we build them: against the real thing.
We build these for a living
MCP servers and connectors we shipped run in production over SAP, NetSuite and Salesforce. The protocol is the list of everything that has ever bitten us, written down so it does not bite you.
We know where the model guesses
Descriptions that steer the agent to the wrong tool, schemas loose enough to invent a field, retries that post twice. We have watched real agents do all three, and we test for them on purpose.
The environments already exist
Real S/4HANA, NetSuite, Oracle Fusion, Dynamics, Coupa, Salesforce and HubSpot on our side, configured and maintained. Day one is a testing day, not an access-request day.
Validation questions, answered.
The MCP server — repo, package or hosted endpoint — its tool list, and for each tool what a pass looks like. If there are agent tasks you care about, “release the blocked invoices for this vendor”, give us those too and we test them end to end. We do not need your customers’ data or access to any of their systems.
Both, with the same protocol. An MCP server needs everything an API connector needs, plus the agent-specific checks: whether the descriptions lead the model to the right tool, whether the write tools have confirmation gates, whether a retry can post twice. Send us an API connector and we simply skip the agent layer.
No, and we use the same tools ourselves. AI-written connector code is usually good. It carries the same risk as code from any author who has never seen the target system: unchecked assumptions about configuration. We validate it exactly the way we would validate a human-written one.
A coverage matrix of every tool and operation. Pass or fail, with the request, the response and the system-side effect as evidence. Findings ranked by severity, each with a root cause and a concrete fix. Notes on which assumptions are per-instance settings that will break at the next customer. Plus a machine-readable results file and a walkthrough with the engineer who ran it.
The sandbox pass catches platform-level defects, which is where most findings live: real error shapes, auth over time, permission gaps, write mechanics. Customer-specific problems are a design question, and the report tells you which assumptions to turn into up-front checks and rehearsed writes. For an enterprise rollout we can also run the same protocol against the customer’s own sandbox before go-live. Production access is never needed.
Yes, for a few days around the run if it helps you reproduce and fix findings. It is part of an engagement rather than something on its own: what you take away is a validated connector and the evidence behind it.
Usually one to two working weeks for a server with ten to twenty tools, including one retest after your fixes. Scoping is a short call and ends with a fixed quote per MCP server and target system, typically within 24–48 hours.
No. We validate; vendors certify. The report is a dated, point-in-time statement about your connector on a specified system version, configuration and dataset. Plenty of teams use it as the evidence pack for an enterprise security review, and if SAP certification is the goal, it is a good rehearsal for it.
Synthetic data we generate for your tool surface: suppliers, purchase orders, invoices, employees, opportunities, whatever the tools touch. No production data and no personal data enters the environment, from either side.
Fix what matters, send it back, and the retest is included. If you want the suite re-run when the ERP ships a new release or you ship a new version, we can keep it on a schedule. And if the findings turn out to need a rebuild rather than fixes, that becomes a scoped build with the same engineers.
Find out before your customer does.
Tell us which system your MCP server targets and roughly how many tools it has. You get a test plan, a delivery date, and a fixed quote — usually within 24–48 hours.
or email us directly — hello@inovaflow.io