MCP Server Builds for Internal Tooling
Last verified: October 2026· engagement
We expose your internal systems — Datadog, Linear, databases, deploy tooling — to AI agents over MCP, so your devs can work against company infra safely.
- Outcome
- Internal MCP servers with auth, access control, audit logs
- Timeline
- 3–6 weeks
- Pricing
- $25–75k per build, $3–8k/mo maintenance
- Buyer
- Head of Platform, Head of DevEx
The problem
Your devs want to use agents against company infra — Datadog, Linear, internal databases, deploy systems — but there’s no safe, audited way to expose those systems.
What we do
- Build MCP servers for your internal systems with scoped access control.
- Add authentication, authorization, and full audit logging.
- Package them so any agent (Claude, Cursor) can use them safely.
- Document and hand off, with maintenance available if you want it.
How it fits together
What you get
Built on our open source
ormai — Gives AI agents database access without the risk — scoped, governed access for agents.
Why the protocol is the easy part
Getting an MCP server talking to a client is genuinely a weekend of work, and teams who have done that sometimes conclude they do not need help. The part that takes the remaining weeks is everything that has to be true before you point it at production infrastructure: which identity the server acts as, how a request from an agent maps onto a permission your existing systems already understand, what happens when an agent asks for something destructive, and how you reconstruct afterwards who did what.
Our default shape is read-only until proven otherwise. Every tool starts scoped as narrowly as it can be and still be useful, writes require an explicit escalation, and anything irreversible needs a human in the loop. Credentials never live in the repository or in an agent's context — the server holds them and the agent holds a capability to ask. Rate and cost guards sit on the server rather than being trusted to the caller, because an agent in a loop is a much more effective way to exhaust a quota than any human user.
The design decision that recurs is granularity. A thin wrapper that exposes a whole database or an entire API surface as one tool technically works and is a bad idea: the agent has too much latitude, the audit log tells you nothing useful, and every call is a judgement call. A set of narrow, purpose-shaped tools — look up this kind of record, run this class of query, open this sort of ticket — is more work to build and dramatically easier to reason about, govern, and let a team of thirty engineers use without supervision. That trade-off is most of the engagement.
When this is not the right engagement
Getting a server talking is a weekend; the governance is the engagement. It is a poor fit when:
- You want one server that exposes an entire internal API surface. We will argue for narrow tools, and if that is not wanted we are the wrong firm.
- The underlying system has no usable permission model. The MCP server cannot invent one, and building on top of that gap is how agents get too much access.
- It is a public, well-served system with a good community server already. Use that, and spend the budget on the internal one nobody else will build.
Common questions about this engagement
Do you work under NDA?
Yes — we sign your mutual NDA before any data or repo access. For audits we prefer read-only access to start; for builds we work in a clean repo under your ownership.
Will we own what you ship?
Always. You own the code, the runbooks, the dashboards. We are explicitly set up to hand off and transition out, not to create dependency.
Vendor-agnostic — what does that mean in practice?
We integrate with what you already run — OpenAI, Anthropic, open-weight models on your cloud, your CI/CD, your observability stack. If a hosted vendor solves it, we will not reinvent it; if a self-hosted tool is the right answer, we will not pretend the hosted one is.
How is this different from a Big Four consulting deck?
We are the engineers doing the work, not analysts handing recommendations to a different team. The deliverable is working software in your repo, not a slide deck.
Can you work with our in-house AI team instead of replacing them?
Yes — most of our engagements pair with an internal owner and ramp them up to run the system after we leave. Many of our best engagements start with "we hired an AI team, help us get them productive."
Why not just use the community server for this system?
For prototyping you should. The reasons to build are specific: the system is internal and no server exists, the off-the-shelf server exposes far more surface than you want agents touching, or you need least-privilege credentials, read-only defaults, cost and rate guards, audit logs and human approval on destructive actions. If a community server already does the job for a public system, we will tell you to use it and spend the budget on the internal one nobody else will build.
How do you decide how many tools a server should expose?
Narrower than feels efficient. A thin wrapper that exposes a whole database or an entire API as one tool works and is a bad idea: the agent has too much latitude, every call is a judgement call, and the audit log records nothing useful. Purpose-shaped tools — look up this kind of record, run this class of query, open this sort of ticket — take longer to build and are dramatically easier to govern and reason about. That trade-off is most of the design work.
Guides for this work
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in late 2024, that defines one uniform way for an LLM application to connect to external tools and data through a client-server protocol built on JSON-RPC.
MCPHow to build an MCP server
An MCP server is a small program that exposes your tools, data, and prompts to an AI client over a standard protocol — the fastest way to give Claude or Cursor safe, structured access to your systems.
Hiring & partnersHow to choose an MCP server development company
The MCP SDK is a weekend's work; the job you're actually hiring for is least-privilege auth, scoping, audit logging, and production hardening on servers that reach straight into your internal systems.
Let’s scope it on a call
Thirty minutes with an engineer. We’ll tell you straight whether this is the right first move for your team.