AI & data

AI agents that do real work, safely, on your systems.

Agents become useful when they can read your data and act in your tools, and dangerous when they can do so without limits. We build MCP servers and agent workflows with scoped permissions, human approval for risky actions and an audit trail for every step.

AI agents & MCP servers
4–12 weeks

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When to call us

Sound familiar?

01
You want AI assistants like Claude or ChatGPT to work with your internal systems.
02
A repetitive multi-step process could be handled by an agent with human sign-off.
03
Your agent pilot works in demos but nobody trusts it in production.

How Tulmira handles it

Our approach, step by step

1
Map the workflow
We identify which steps an agent can take alone, which need approval, and which must stay human.
2
Design the tools
MCP servers that expose your data and actions with clear tool descriptions, narrow permissions and OAuth 2.1.
3
Add guardrails
Input checks, action limits, approval steps and a full audit log of every tool call the agent makes.
4
Evaluate and operate
Scenario tests before release, then monitoring of success rates, costs and escalations in production.

Our standards

Non-negotiable practices

Least-privilege access for every agent and tool
Human approval for actions that spend money, send messages or delete data
Every tool call logged and attributable
Prompt-injection defences on all external content
Scenario-based evaluation before every release
Schema change detection on the MCP servers you depend on

What you get

Production MCP servers for your systems and data
Agent workflows with approval steps and guardrails
Audit logging and monitoring dashboards
Evaluation scenarios and a runbook for operators

Tools we use for this

MCP
Claude API
OpenAI API
TypeScript
Python
OAuth 2.1

Proof

Built the same way we build our own products

Proxar

Developer Tools

Proxar watches MCP servers for breaking changes; we build MCP integrations the way we would want to monitor them.

See Proxar →

FAQ

Common questions

Anything else, ask us directly.

The Model Context Protocol is an open standard that lets AI assistants use your tools and data. An MCP server is the secure adapter between an assistant and one of your systems.