Let AI agents use your systems safely.
Production MCP servers and custom tools that expose your data and actions to AI assistants — with authentication, scoped permissions, audit trails and limits — so agents can do real work without becoming a new attack surface.
- Tool design
- Build read-only first
- Add actions with checkpoints
- Operate and extend
Every tool call is attributed to a human.
AI assistants are becoming the interface people use to get work done: they ask the assistant, and the assistant is expected to look things up and act. The Model Context Protocol (MCP) is the open standard that lets an assistant call your systems as tools. If your software has no tools, it is invisible to that interface — whether the assistant is Claude, ChatGPT, Copilot or one your enterprise runs itself.
Exposing systems to agents is an engineering problem before it is an AI problem. A tool that can read a customer record or post a transaction needs authentication, permissions scoped to the user the agent acts for, rate limits, an audit trail and a clear line between what the agent may do alone and what needs a human. We build MCP servers and tools to that standard — for software vendors who want their product inside the assistant, and for enterprises who want their own agents to work across their estate.
Every tool call is attributed to a human, logged, and bounded by what that human could do themselves. Agents get no more authority than the person they act for.
Four ways tools reach your systems.
Most engagements start with a read-only server over one system, then add actions as the governance proves itself.
MCP servers for your product
If you sell software, an MCP server lets your customers' assistants read from and act on your product. Designed with your API team, versioned, documented and tested against the major assistants.
Enterprise tool layer
A governed set of tools over your internal systems — CRM, ERP, ticketing, data warehouse — so an internal agent can answer and act across them with the caller's permissions, not a service account's.
Agent workflows
Multi-step agents that use those tools for a defined job: triage a ticket, prepare a renewal, reconcile a discrepancy — with checkpoints where a human approves before anything irreversible happens.
Retrieval as a tool
Your documents exposed to agents through a permission-aware retrieval tool, so the assistant cites policy rather than guessing. Built on the same stack as our knowledge retrieval work.
How the work runs, day to day.
The agent may do what the user may do, and no more.
Tool access inherits the identity of the person the agent acts for, through your existing identity provider. Each tool declares what it reads and what it changes; changing tools require an explicit grant and, where the action is irreversible, a human confirmation step. Every call is logged with the user, the agent, the tool, the input and the result.
- OAuth / OIDC against your identity provider; no shared service accounts
- Read tools and write tools separated, with write tools granted per role
- Rate limits, cost limits and kill switches per tool and per tenant
How the work runs.
Tool design
Which systems, which operations, which users. The tool contracts are written and reviewed with your security team before code.
Build read-only first
The server with authentication, permissions and audit, exposing read operations. Tested against the assistants you target and against your own agent.
Add actions with checkpoints
Write operations with grants and confirmation steps. A pilot group uses the agent for real work; the logs are reviewed together.
Operate and extend
Monitoring, versioning and new tools as the use cases prove themselves. We run it or hand it over with runbooks.
What you keep.
- MCP server(s) in your environment, versioned and documented
- Tool contracts with declared reads, writes and limits
- Authentication through your identity provider and per-call audit logs
- Test suites run against the assistants you target
- Monitoring, rate limits and kill switches, with runbooks
When this is the right call.
Choose this when your customers or your staff are already asking assistants to do work that needs your systems, and the question is how to let that happen without a service account with god rights.
Look elsewhere if there is no clear job for an agent yet. A tool layer with no use case is infrastructure nobody calls; start with AI-First Engineering to find the job first.
Frequently asked questions
Services that pair with this.
Which system should your assistant be able to use?
Tell us the system and the job. An engineer reads it and replies in writing with a view of the tools, the governance and the first release.