Custom MCP Servers

Why Work With Us

A Model Context Protocol server is the governed bridge between an AI assistant and a system you already run. Rather than pasting data into a chat window or wiring a bespoke integration for every model you try, you expose your system once, through an open standard, and any MCP-capable assistant can use it.

The protocol defines three things a server can offer. Tools are actions the model can take — create a record, run a query, publish a page. Resources are data the model can read, from a database table to a document store. Prompts are reusable instructions that package how your organisation wants a piece of work done. Servers connect over stdio for local processes or streamable HTTP for remote ones, which is what makes the same server usable from a desktop client, a browser, or your own application.

MCP is no longer a single vendor’s project. In December 2025 Anthropic donated it to the Agentic AI Foundation under the Linux Foundation, co-founded with Block and OpenAI and supported by Google, Microsoft, AWS and Cloudflare. That matters commercially: the connections you build today sit on a standard with neutral governance and first-class support across Claude, ChatGPT, Copilot, Gemini, Cursor and VS Code, rather than on one company’s roadmap.

Five MCP servers we have delivered into production

Most firms offering MCP development are describing work they have not done yet. These are connections we have designed, built and deployed for clients — each one replacing manual work inside a system a business depends on every day:

• Workamajig — utilisation and burn tracking that previously meant living inside the project system and assembling reports by hand. The connection returns the same picture from a plain-language request, in seconds.
• Track Rabbit + Stripe — an event platform operated without an admin interface. Scheduling, registration and payments are driven conversationally through the connection instead of through screens somebody had to build and maintain.
• HubSpot + Salesforce — the B2B lead pipeline end to end. Inquiries are captured, evaluated, and written back into the CRM and sales tooling without a person in the middle.
• eBay — an enterprise reseller operation where listing, pricing and fulfilment steps run through the connection rather than through manual work in the marketplace UI.
• Web content — publishing, updating, scheduling, swapping assets and wiring up forms, all handled by prompt instead of inside a content management system.

The HubSpot and Salesforce work is worth calling out for a specific reason. Both vendors now ship their own MCP servers, so we have built against the same systems that offer an off-the-shelf option — which means we can tell you honestly when the vendor’s server is the right answer and when it is not.

Should you build one, or use the vendor’s?

This is the question most buyers should ask first, and it is the one almost nobody in this market answers. Salesforce, HubSpot, Slack, GitHub and others publish official MCP servers. Where one exists and covers what you need, use it — we will tell you so, and help you deploy it safely.

A custom server earns its place in four situations:

• The system has no official server. This covers most line-of-business software, and all internal tooling.
• The official server exposes the wrong surface — broad read access when you need three narrow, audited write actions, or vice versa.
• The work spans several systems at once, and you want one governed connection that reflects your process instead of four disconnected ones the model has to reason across.
• Your governance requirements exceed what a general-purpose server offers: per-team scoping, field-level redaction, approval gates on specific actions.

Where MCP servers pay off first

The strongest first candidate is almost always a system your team spends time clicking through to produce something predictable. A few patterns come up repeatedly:

• Reporting that lives inside a UI. Utilisation, burn, pipeline, campaign performance — numbers somebody assembles by hand every week because the system will not simply answer the question.
• Operational workflows spanning two systems. Anything where a person is the integration, copying between a CRM and a marketing platform, or a project system and a finance tool.
• Content and configuration work. Publishing, scheduling, updating metadata, wiring forms — high-volume, low-judgement work currently done through screens.
• Internal knowledge with access rules. Making institutional documentation answerable, with each team reaching only what it should.
• Intake and qualification. Inquiries arriving from a website or inbox that need evaluating and routing before anyone should spend time on them.

A useful test: if somebody could describe the task in a sentence but it takes fifteen minutes of navigating to complete, it is a strong candidate. If the task genuinely requires judgement, keep the person and give them a Tool that removes the mechanical part around it.

How we build them

We start with the workflow, not the software. The first session identifies work your people currently do by hand inside an interface, and decides which of those steps should become Tools, which should stay with a person, and which should stop existing. That scoping determines everything downstream, and it is where most of the value is decided.

From there we design the contract — the specific Tools, Resources and Prompts the server exposes, and the permissions attached to each. We build against the official SDKs, test with the MCP Inspector and with the actual assistant your team uses, and deploy with monitoring and audit logging in place. Then we author the Skills that sit on top, so the capability arrives as something your people can run in plain language rather than as an API somebody still has to learn.

We stay alongside the rollout. A connection nobody adopts returns nothing, so the engagement includes coaching, guardrails and the change management that moves a team from experimenting to depending on it.

Security and governance

An MCP server is a new door into systems that matter, and it deserves more than a list of reassuring words. The specific things we build in:

• Scoped permissions per tool. Each Tool gets the narrowest access that lets it work. Read and write are separated, and destructive actions are separated again.
• Human-in-the-loop on consequential writes. Actions that move money, send communications, or change customer records can require explicit confirmation rather than firing autonomously.
• Prompt-injection defence. Content returned from a tool is data, not instruction. Servers are built so hostile text inside a record cannot redirect the assistant into taking actions on its behalf.
• Full audit logging. Every call, argument and result is recorded, so you can answer what the AI did, when, on whose behalf, and with what result.
• Secrets handled properly. Credentials live in a managed store with rotation, never in prompts, configuration files, or the model’s context.

What it costs

Custom MCP server development starts at $2,500. That covers a scoped, production-ready connection to a single system: the Tools and Resources agreed in discovery, authentication and permissions, audit logging, and handover to your team.

Cost moves with the number of systems involved, how much of the work is read versus governed write, and whether the engagement includes Skills authoring and team enablement on top of the connection itself. Multi-system builds and enterprise deployments with dedicated governance requirements are scoped individually. We will give you a fixed number before any work starts.

Most clients begin with one connection to a system that is causing daily friction, prove the value, and expand from there. Impact begins as soon as the first server goes live, so there is no long build with nothing to show partway through.

Frequently asked questions

How is an MCP server different from an API integration we already have?
A traditional integration connects two systems on a fixed path you specified in advance. An MCP server exposes capability to a reasoning model, which decides at runtime which tools to combine for the request in front of it. Build one server and every MCP-capable assistant can use it, rather than rebuilding the integration for each new tool your teams adopt.

Which AI assistants can connect to it?
Any MCP-capable client. That currently includes Claude, ChatGPT, Microsoft Copilot, Gemini, Cursor and VS Code, among others. Because the protocol is open and vendor-neutral, the server you build is not tied to the model you start with — that is much of the point.

What happens when the protocol changes?
MCP is governed by the Agentic AI Foundation under the Linux Foundation, with versioned specification releases rather than unannounced breaking changes. We build against the official SDKs so that spec updates arrive as dependency upgrades. We also tell you plainly which parts of a build are stable and which sit on newer surface area.

How long does a first connection take?
A single-system server is typically weeks, not quarters. The pace is set by how quickly we can get access to the target system and agree the permission model with whoever owns it, more than by the build itself.

Do we need to move to a different AI platform?
No. We build to the standard, not to a vendor. If you have standardised on one assistant we will build and test against it; if you have not decided, the server keeps that decision open.

Can it work with our internal or legacy systems?
Yes, and this is usually where custom work pays for itself. Systems with an API, a database, or even a scriptable interface can be exposed as Tools and Resources. Internal software that no vendor will ever write a server for is exactly the case a custom build exists to solve.

Who owns and hosts what we build?
You own it. We build and can host the foundation, and you keep the keys, the credentials and the code. The intent is that your team ends up able to run and extend it.

What do you need from us to start?
Access to the target system or a sandbox, whoever owns its permission model in the room for scoping, and a clear description of the manual work you want to stop doing. That is usually enough for a first session.

Why Trellist for this work

We have delivered five MCP servers into production for clients, which is five more than most firms selling this work can point to. That experience decides the things that matter: which workflows are worth connecting, where the permission boundaries belong, and what actually gets adopted once it ships. We pair the connection with the Skills your people run and the enablement that makes them stick, and we stay engaged until your team can carry it.

Let’s talk

Bring us the system your team spends the most time clicking through. We will tell you whether an MCP server is the right answer, whether an official one already covers it, and what a first connection would take.