MCP Server Builds for Internal Tooling
Last verified: June 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.
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."
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.