MCP Integration & Development Services
Connect ChatGPT and other compatible AI tools securely to your business systems, data and workflows. Scorchsoft builds production-ready MCP servers, connectors and the portal and API infrastructure behind them.
Connect ChatGPT to the systems that run your business
Many teams already want to use tools such as ChatGPT with their own business information. The trouble is that the useful data lives across a CRM, an ERP, databases, portals, document stores and third-party systems, and copying it into an AI assistant by hand is slow, hard to govern and cut off from live processes.
Scorchsoft builds an integration layer and a secure MCP server that give compatible AI applications controlled access to approved business information and tools. Instead of pasting data into a chat window, an authorised user can ask a question and the AI reaches the right capability directly, within the permissions you set.
The path runs: business systems, then a Scorchsoft portal or integration layer, then a secure MCP server, then ChatGPT and other compatible AI clients.
What is MCP?
Model Context Protocol, or MCP, is a standard that lets compatible AI applications discover and use tools and information that another system chooses to expose.
A simple way to picture it
An API traditionally lets one software application talk to another. An MCP server makes a chosen set of capabilities available in a form that compatible AI applications can discover and use, so an AI client can find out what tools exist and call them in a consistent way.
MCP does not replace APIs. An MCP implementation usually sits on top of your APIs, application services and existing integration architecture, exposing selected capabilities from them rather than reinventing what they already do.
What it owns, in one line
This capability is about one thing: exposing selected business information and actions to compatible AI applications through a controlled Model Context Protocol interface.
It sits alongside broader AI integration, AI agents and API integration, and works best when it draws on the same well-built foundations those rely on.
How an MCP Integration Works
From the capabilities you choose to expose, through a governed portal layer, to the AI client that calls them — with control built in at every step.
What an MCP integration can do
Picture a company with a Scorchsoft-built internal portal. The portal already authenticates users and talks to the CRM, ERP, operational databases and other systems. We add an MCP server that exposes a carefully chosen set of the portal's capabilities.
An authorised user connects that MCP server to a compatible ChatGPT environment, and can then ask things like:
- Which sales opportunities need attention?
- Show me the status of customer ABC
- Summarise this week's operational exceptions
- Find documents associated with project 123
- Create a draft note against this customer
- Start the approved onboarding workflow for this account
The AI does not receive unrestricted database access. It uses the specific tools and information the system has deliberately exposed, and nothing more. That distinction is the heart of a good MCP integration.
MCP architecture, with control built in
The pattern that makes MCP safe and reusable: AI reaches your systems only through a governed portal and application layer, and only through the tools the MCP server deliberately exposes.
- Business data and systems — CRM, ERP, operational databases, documents, data lake, third-party APIs.
- Scorchsoft portal / application services — authentication, permissions, business logic, integration, validation, audit.
- MCP server — approved tools, resources, actions.
- AI — ChatGPT, AI agents, other compatible MCP clients.
Permissions and business rules live in the portal and application layer, in deterministic code, not in the AI. The MCP server exposes only what that governed layer allows, which is what keeps the whole arrangement controllable.
Scorchsoft's portal-led MCP approach
Our key difference is that we do not just write an MCP wrapper around a database. We can build the underlying business portal, services, APIs, authentication, data architecture and integrations, as well as the MCP layer on top.
One powerful approach is to create or extend a secure business portal that acts as an integration layer over your existing systems. That layer handles authentication, permissions, business logic, validation, data normalisation, API orchestration, audit trails and workflow controls, and exposes reusable application services. MCP then publishes appropriate capabilities from this governed layer.
Reusable capabilities, not an isolated connector
The same layer can serve web portals, mobile apps, dashboards, automation, integrations, internal software and AI agents. So you are not building a throwaway "ChatGPT connector": you are creating reusable business capabilities that many interfaces can consume, one of which happens to be MCP. A portal is not mandatory, though. Where you already have suitable APIs or application services, we integrate with those instead.
Read and write capabilities
An MCP server can expose both information and actions. Each capability is designed and permissioned on purpose, rather than handed over wholesale.
Read capabilities
Retrieve a customer, search documents, inspect an order, view project information, query operational metrics or retrieve account activity.
Write and action capabilities
Create a note, update an approved field, raise a support ticket, start a workflow, prepare a report, send information into another system, or request an action that needs approval. Write access is always deliberate, and never a blanket permission to change whatever the AI likes.
Security and permissions
MCP endpoints are production application interfaces and are built like them. MCP is not inherently secure or insecure: security comes from how the surrounding authentication, authorisation, application logic and infrastructure are designed. Nine controls do the work:
- Authentication — the MCP service knows which user or application is connecting before anything else happens.
- Authorisation — users reach only the information and tools appropriate to them, never a blanket view.
- Role-based access — where it fits, permissions follow the same roles used by the business portal or underlying application.
- Tool-level permissions — different people can be granted access to different MCP tools, not an all-or-nothing set.
- Read vs write — information retrieval is separated from actions that change data, and writes are granted deliberately.
- Approval workflows — sensitive actions can require explicit human confirmation before they proceed.
- Validation — arguments supplied by the AI are validated by deterministic application code before any action runs.
- Auditability — important operations are logged, so you can see what was accessed and what changed.
- Rate limiting and controls — endpoints carry the operational controls expected of any production interface.
We avoid the "point ChatGPT at your database" pattern. Rather than letting an AI query production data freely, requests flow from the AI to a deliberately exposed MCP tool, then to a business or application service, and only then to the authorised data source. That keeps permissions and business rules inside deterministic application code, where they belong.
MCP and your existing APIs
MCP and APIs solve related but different problems, and they work together rather than competing.
APIs provide structured interfaces between software systems. They are how applications have integrated with each other for years, and they remain the backbone of most integrations.
MCP provides a standard interface designed to make tools and resources discoverable to compatible AI applications, so an AI client can find and use them consistently.
The layers stack: existing systems, then APIs and services, then the MCP server, then the AI client. We can build any or all of them. See our API & Systems Integration capability for the foundations MCP builds on.
MCP and data ecosystems
MCP becomes far more powerful when a business already has well-connected systems. If your CRM, ERP, documents, operational software and bespoke applications have sound integration architecture, the same capabilities can be exposed to portals, apps, automation, reporting, AI agents and MCP clients alike.
The sensible order is to connect the business first, then give AI controlled access to the right parts. That does not mean a huge transformation programme up front. We can start with one valuable MCP use case and extend the data ecosystem incrementally as the value proves itself.
MCP and data lakes
Some MCP use cases benefit from historical or analytical data that is unsuitable to pull straight from transactional systems.
- CRM and ERP hold operational and live information: the current state of customers, orders, projects and day-to-day activity.
- A data lake holds durable, large-scale historical information suited to trends, investigations and management analysis.
MCP tools can expose appropriate capabilities across both, so a user might compare current performance with historical trends, investigate anomalies, retrieve past events or produce a management summary from curated data. MCP does not require a data lake; a lake simply becomes useful where the business needs durable historical information for analytics and AI.
Practical Examples
Five scenarios showing controlled access in action, each mediated by application services and permissions.
Opportunities going quiet
Sales / CRM. A salesperson asks which opportunities have had no activity for 14 days. The MCP tool calls a controlled CRM integration and returns only records that authenticated user can access, then drafts updates for the top three, with no manual exporting.
What's delayed, and why
Operations. A manager asks which customer jobs are currently delayed and why. An MCP tool retrieves the information from operational systems and presents it through the AI interface.
A complete account picture
Customer information. A staff member asks for a full summary of a customer. The underlying service combines authorised information from CRM, ERP, support and the customer portal into one answer.
This year versus last
Historical analysis. A manager compares this month's support workload with the same period last year. Current data comes from operational systems; historical data is retrieved from a data lake.
Creating a record, safely
Controlled action. A user asks to create a follow-up task for next Tuesday. The MCP server exposes a controlled create-task action, and the application validates permissions and inputs before writing the record.
Your workflow here
The right first use case is usually a specific, high-friction task your team does often. Describe it and we will scope a controlled MCP tool for it.
Learn moreMCP for AI agents
MCP is useful for AI agents as well as chat clients, but the two are not the same thing.
An agent may use MCP tools to interact with your systems during a multi-step workflow. MCP supplies the tools and context; the agentic behaviour — the planning and the sequencing — is a separate concern. In other words, MCP is not a synonym for an agent. Where you need AI to carry out multi-step work across systems, our AI Agents & Automation capability covers that, often consuming the very same MCP tools built here.
Start with one valuable use case
You do not need to connect everything before you see value. Once business capabilities are exposed cleanly through APIs and services, they can be reused by web and customer portals, mobile apps, internal systems, automation, AI agents and MCP clients. As more systems become connected, the available capabilities become more useful, so you are building reusable business infrastructure rather than a collection of isolated AI integrations. We recommend starting with one high-value MCP use case and extending from there.
Why Scorchsoft is well placed to build this
Scorchsoft can build both the MCP interface and the systems behind it. That is what lets a project go beyond shallow connector development.
Our capabilities span custom web portals, API development, third-party integration, backend development, authentication and SSO, database development, data lakes, AI integration, AI agents, cloud infrastructure and security-aware application architecture. Because the same team can build the governed layer and the MCP layer on top of it, the result is an integration you can trust in production and extend over time.
How Scorchsoft Implements MCP
1
Identify the use cases
Identify valuable AI use cases worth starting with.
2
Map the systems
Identify the systems and information those cases need.
3
Review what exists
Review your existing APIs and architecture.
4
Design the capability layer
Design the appropriate business capability layer.
5
Build or extend the portal
Build or extend the portal and services where required.
6
Authentication and permissions
Implement authentication and permissions.
7
Expose scoped MCP tools
Expose deliberately scoped MCP tools and resources.
8
Connect and test
Connect and test with suitable MCP clients.
9
Audit and monitoring
Add audit, monitoring and operational controls.
10
Extend over time
Extend with additional capabilities over time.
Tell Us the First Job You Want AI to Reach
Start with one high-friction task your team does often. We will scope a controlled MCP tool for it, design the permissions around it, and build the portal and API layer underneath if you need one.
Frequently Asked MCP Questions
Model Context Protocol, or MCP, is a standard that lets compatible AI applications discover and use tools and information that another system chooses to expose. It gives AI clients a consistent way to find and call approved capabilities.
An MCP server is the service that publishes a chosen set of tools, resources and actions over the protocol, so compatible AI applications can use them. It usually sits on top of your existing APIs and application services.
In practice, an MCP connector is the piece that links a specific AI client to an MCP server, letting that client discover and call the exposed capabilities. Scorchsoft builds the server and the surrounding infrastructure it relies on.
Yes. That is the core use case here. We expose a deliberately chosen set of capabilities through an MCP server, and an authorised user can connect it to a compatible ChatGPT environment, within the permissions you set.
Yes. We build custom MCP servers tailored to your systems, along with the portal, APIs, authentication and data architecture behind them where those are needed.
Yes, through a controlled integration. MCP tools call application services that talk to your CRM or ERP, returning only what the authenticated user is permitted to see or do.
Yes. Where historical or analytical data is useful, MCP tools can expose capabilities that draw on a data lake as well as live systems. A data lake is not required for MCP.
Yes. A common approach is to expose capabilities from a secure portal that already handles authentication and business logic. We can use your existing portal or build and extend one.
No. MCP usually sits on top of APIs and services, exposing selected capabilities to AI clients. APIs remain the backbone of software-to-software integration.
Yes, when you want it to. Write and action capabilities are designed and permissioned deliberately, kept separate from read access, and sensitive actions can require human approval.
Access is limited to the specific tools and information the MCP server exposes, governed by authentication, authorisation, role-based and tool-level permissions, and validation in application code. The AI never gets unrestricted access to underlying systems.
Yes. Permissions can follow the roles used by your portal or application, so different people can access different tools and data through the same MCP server.
Yes. Sensitive or hard-to-reverse actions can require explicit human confirmation before anything changes. Automation does not have to mean autonomy.
Usually not. Where you already have suitable APIs or application services, we integrate with them. Where you do not, we can build or extend the governed layer MCP needs, incrementally.
Yes. We regularly work with systems built or maintained by others, through their APIs or supported interfaces, and can collaborate with your existing suppliers where sensible.
Yes, and we recommend it. Start with one valuable use case, prove it in real use, and reuse the same foundations for the next. The capabilities you expose become reusable across portals, apps, automation and other AI clients.
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What Our Clients Say
Scorchsoft helped us take our idea for an app and make it a reality. Everything from the planning meeting to decide what we really needed to the project management and execution was great. It was delivered on time - early in fact - and on budget. Highly recommend.
Rebecca PalserDragonfly IntelligenceScorchsoft is a brilliant company with fantastic knowledge of the mobile app industry. From the project management to the development team, they have been the perfect candidate for our project, and we can't thank them enough!
Lance ChorltonGapped OnlineWe're really pleased with the work Scorchsoft has done in developing our web portal! They have been accurate with timelines and budget, delivering a solid product that allows us to monitor and manage patients remotely while they use our novel medical device at-home. The "plan - design - build" approach has worked well and saved us time in the long-run by catching requirements and issues early.
Daniel GreenSensTrainI'm really pleased with how my app came out, it was exactly what I was looking for. The team at Scorchsoft are great at what they do and made the whole process as simple and easy as possible. Being someone who is not very tech savvy the set up and back end operations were done in a great easy to use manner even for myself which makes using my app stress free. Thanks to all the team!
Ruben CarrollMosaic MasterpiecesThe new Flourish Education website has already removed a lot of manual processes, freeing up both schools, candidates and internal employees time. We are delighted with the look and feel which is clean, professional and more engaging. We are also pleased with the decision to have an HD video background on the homepage, and building immediate trust with our clients by giving them a taste of what it looks like in the Flourish Education offices.
James HancocksMarketing Manager, Flourish Education I can't believe how quickly we started to see results with this project. Scorchsoft provided us with graphic-designed mockups of how the app would look once built, and we were able to sell the product for use by our first customer before the product was finished. Since launching in March, we have secured a major television network as a client who now uses Image Approvals to manage the talent approval process for their productions.
Aimee SpinksMD, ImageApprovals.com
Need help building your ideas?
Tell us where you're headed and we'll come back with our thoughts, a realistic plan and a rough cost estimate. Scorchsoft is a UK-based team of app, portal and AI developers, working in-house from Birmingham's Jewellery Quarter.