Summary: Data security teams are being asked to govern environments that are growing faster than any manual process can keep up with. We built the ALTR MCP server to change that equation. It connects any MCP-compatible AI agent directly to ALTR’s full API surface, so the routine work of auditing, enforcing, and reporting on your security posture can happen through natural language, at the speed your environment actually moves.
We have been API-first since day one. Every action in the ALTR platform, every policy, every masking rule, every classification tag, every access control, has always been available as an API call. That was a deliberate decision, and it has driven a lot of how we think about building software. If you can do it in the UI, you should be able to do it in code. Full stop.
So, when the MCP standard started gaining real traction, we paid attention. Not because it was a trend, but because it pointed at something we had been working toward for a long time: a world where your data security platform is not something you log into, but something your tools and agents interact with directly.
We built an MCP server for ALTR. We open sourced it. And we think it changes what is possible for data security teams in a pretty fundamental way.
What MCP Is and Why It Matters for Security Teams
MCP stands for Model Context Protocol. It is an open standard that lets AI agents communicate with external tools and services in a structured way. Think of it as a universal connector between an agent and the software it needs to take action in the world.
Before MCP, getting an AI agent to interact with a platform like ALTR meant building a custom integration. Someone had to write the code, maintain it, and keep it in sync as the platform evolved. That is real engineering work, and it creates a ceiling on how broadly this kind of automation can be adopted.
MCP removes that ceiling. Any agent that supports the protocol can talk to any server that implements it. The ALTR MCP server is our implementation. It makes our full API surface available to any MCP-compatible agent, which means teams using Claude, or any other agent that supports the standard, can interact with ALTR directly through natural language.
No custom integration. No middleware. No translation layer. Just your agent talking to your data security platform.
What the ALTR MCP Server Actually Does
The ALTR MCP server gives an AI agent access to everything in our platform. Classification. Dynamic data masking. Access policies. Rate limiting. Audit logs. Tokenization controls. If it lives in ALTR, an agent can read it, query it, and act on it.
That means a security team can ask their agent to pull a complete view of their current data security posture and get a real answer. They can ask it to compare that posture against a compliance requirement, identify what’s missing, and apply the controls that close the gap. They can ask it to generate an audit-ready report of everything that was done. All of that happens through conversation, against a live environment, with real consequences.
We want to be clear about what that is and what it is not. It is not a summarization tool that surfaces insights about your security data. It is the platform itself, operating through a natural language interface. When an agent applies a masking policy through the MCP server, that policy is applied. When it updates an access control, that control is live. The agent is not drafting a recommendation for a human to act on later. It is doing the work.
Why We Open Sourced It
We could have shipped this as a closed feature. We did not, and the reasoning was straightforward.
Data security teams are operating in environments that look different from each other. Different database platforms, different agent frameworks, different compliance requirements, different internal workflows. A closed implementation would work for some of those teams and not for others. An open source implementation means teams can inspect it, extend it, and adapt it to fit their specific environment.
It also means we are accountable to the community in a way that matters. If something does not work the way it should, the people who depend on it can see why and help fix it. That kind of transparency is consistent with how we think security tooling should work.
And honestly, we think MCP is going to be significant infrastructure for how enterprise software works going forward. Being an early, open contributor to that ecosystem is important to us. We want to help shape what good looks like, not just benefit from it.
The API-First Foundation That Makes This Possible
We mentioned this at the top, but it is worth being direct about: the MCP server only works this way because of how ALTR was built.
Platforms that were designed primarily for human interaction, dashboards, point-and-click workflows, manual configuration, cannot simply bolt on an MCP server and get the same result. The agent can only do what the API supports. If the API is limited, the agent is limited.
Because every ALTR capability is API-accessible, the MCP server inherits the full surface of the platform. There is no reduced feature set, no “agent mode” with limited functionality. An agent using our MCP server has access to the same capabilities as a security engineer using our platform directly. That parity is intentional and it is not something every platform can offer.
What This Changes for Data Security Teams
The teams we work with are good at their jobs and stretched thin. A lot of them are managing complex data environments with lean headcount. They know what good governance looks like. The constraint is not knowledge, it is time and bandwidth.
The ALTR MCP server directly addresses that constraint. Routine compliance work, auditing your current state, applying policy updates, generating reports, checking coverage gaps, can be handled by an agent working through natural language. That frees the people on the team to focus on the decisions that actually require their expertise.
It also changes the speed at which governance can respond to change. A new regulatory requirement drops. A new data source gets added. A new team needs access configured. Historically, each of those events kicks off a manual process with a timeline attached. With an agent that has direct access to ALTR, the timeline compresses significantly. The work that used to take days can happen in a single conversation.
We also built the server to support oversight. Agents can be instructed to ask for confirmation before making significant changes, to flag gaps that require human judgment, and to report on everything they did. The goal is not to remove the security team from the equation. It is to give them better leverage over the work they are already responsible for.
This Is the Direction We Are Moving
The ALTR MCP server is not a side project or an experimental feature. It reflects how we think data security tooling needs to evolve. The interface for doing security work is changing. Agents are becoming a real part of how teams operate, and the platforms those teams depend on need to be accessible to agents in the same way they are accessible to people.
We built our MCP server to meet that moment. It works across the cloud data platforms our customers are running today, and it is designed to work alongside the native MCP servers those platforms offer. The vision is a unified agent workflow that spans your entire data environment, governed consistently, enforced automatically.
Natural language is a legitimate interface for data security now. Not a shortcut, not a demo trick. A real way to operate your security program. We built the infrastructure to make that true, and we think it matters.