MCP · In private beta
Tools, not training data.
The Corthos MCP server exposes the data layer as Model Context Protocol tools, so AI agents pull grounded data at inference time instead of guessing from what they were trained on. Definitions, lineage, and source pointers come back with every call.
Who it's for
Anyone building agents in Claude, Cursor, Copilot, or in-house frameworks who needs the model to reason about real entities — institutions, employers, places — and not invent the answer. MCP gives the agent a discoverable surface of tools that ground every response in source data.
It pairs with the API for teams that want both: API for application code that knows exactly what it needs; MCP for the agent layer where the model decides what to fetch.
What's in the MCP server
The layer, exposed as tools.
| Capability | What it means |
|---|---|
| Layer-as-tools | Entity lookup, relationship traversal, cohort queries, and time-series retrieval are exposed as discoverable MCP tools. Your agent reads the tool schemas, picks what it needs, and calls. |
| Definitions exposed alongside data | Every tool response carries the metadata the model needs to reason — definitions, units, valid ranges, last-refresh timestamps. The agent doesn't have to guess what a column means. |
| Source pointers in every response | Tool outputs include lineage so the agent can cite. When the model produces an answer, the underlying record traces back to a specific source — no fabrication. |
| Compatible with any MCP client | Claude, Cursor, Copilot, in-house agents — any MCP-aware client connects with no special integration work. Standard protocol, standard transport. |
| Stateless, idempotent calls | Tool calls are stateless and safe to retry. Caching, batching, and parallel invocation are straightforward to layer on. |
| Per-deployment access controls | Scope which tools and which data slices each MCP server exposes. Run a focused server for one product, or a broad one for an internal agent platform. |
What you can build on top
Domain-aware Claude / Cursor agents
Plug the MCP server into any MCP-aware client and the agent gains grounded retrieval over real entities, with citations attached.
Internal agent platforms
Build a research, analysis, or decision-support agent for your team that operates on a defendable foundation — not whatever the model remembers.
Workflow agents
Multi-step agents that walk relationships, compare cohorts, and assemble grounded answers across tool calls — without inventing data along the way.
Embedded copilots
Embed an agent inside your own product whose answers are always traceable back to source — and stay current as the layer refreshes.
Enterprise Engagement Model
Our proven three-phase approach to enterprise transformation
- 1
Assessment
We evaluate current data assets, flows, and decision points.
- 2
Blueprint
We design your Corthos OS integration map, guarantees, and SLAs.
- 3
Build
We implement, validate, and operationalize the enterprise rollout.
Bring grounded data to your agent.
Get in touch to discuss how the Corthos domain-intelligence layer fits your data, your domain, and the AI products you're building.