MCP Server
Your agents get what your investigators get.
MCP connects the agent. DataWalk decides what it sees: resolved entities, mapped relationships, live data, and only what the caller is already cleared for.
Every request runs under the caller’s DataWalk credentials, inside your environment, with permissions enforced at execution and every DataWalk tool call logged for review.
“Agents with governed, contextual access to the right data deliver trustworthy insights. Without it, they misinterpret, hallucinate, and erode trust.”
— Aga Kopytko, reporting from Gartner D&A Summit 2026
Most AI pilots don’t fail in the pilot. They fail in production review.
The demo works. The model performs. Users see value. Then security, compliance, and architecture teams start asking the questions that decide whether the project ships.
Most agentic AI pilots stall exactly here. The DataWalk MCP Server answers those questions by carrying identity and permissions through execution, recording every action, and keeping the platform inside the environment you control.
- 01Who performed the query?
- 02What permissions were used?
- 03Can the result be reconstructed?
- 04Can we prove how the answer was generated?
- 05Can we trust the underlying data?
The Architecture Behind AI That Ships.
DataWalk gives AI agents a controlled way to use the platform, not open access to the data beneath it. The MCP Server exposes defined DataWalk capabilities, checks each request before it runs, and returns current results under existing permissions. The knowledge graph supplies the resolved entities, relationships and meaning behind those results.
MCP gives agents a standard way to call tools. DataWalk gives those tools a governed source.
Each call runs against a defined tool contract, returns live DataWalk data, and inherits the caller’s existing permissions.
Right information. Right person.
The agent inherits the caller’s permissions. No parallel access model, no data the user could not already see. Malformed or invented arguments are rejected at the tool contract, not answered around.
Relationships already mapped
Resolved entities and known connections come from the graph, so the agent pulls the connected subset it needs instead of flooding its context with raw records and losing the signal in the noise.
Business meaning preserved
The graph carries the ontology investigators already trust, not rows and columns an agent has to reinterpret.
Every call is on the record
Each DataWalk tool call is logged, so a reviewer can see exactly which queries the agent ran during validation.
Where Teams Apply It
Financial Crime
Alert triage and case documentation, attributed to the analyst.
Law Enforcement & Intelligence
Plain-language questions on the investigation graph, air-gapped included.
Government
Agent access where sovereignty and accountability are non-negotiable.
AML/KYC
SAR drafting and KYC enrichment that survive a regulator's reconstruction.
What It Does
Uses Your DataWalk Access
The agent can use only the tools and information available to the identity behind the request.
Ask in Plain Language
Search, investigate and invoke DataWalk capabilities from the AI tools your teams already use.
Entities Already Resolved
DataWalk returns resolved entities and relationships instead of asking the model to reconcile records for itself.
Meaning You Maintain
Your definitions, rules and provenance remain part of the context rather than being inferred again on every request.
Governance Stays in Force
Permissions, attribution and audit remain active throughout execution.
Build Once. Reuse Across Agents.
The same governed knowledge can support new agents, models and use cases without rebuilding the context each time.
Deploy inside your environment.
Keep the DataWalk platform and MCP Server inside the environment you control, with customer-managed agent and LLM services.
- Where
- On-premises, private cloud, hybrid, or air-gapped.
- LLMs
- OpenAI, Anthropic, Gemini, Llama, and more. Or locally hosted endpoints.
- Clients
- Claude, Copilot, Cursor, LangGraph, Azure AI Foundry, Vertex AI, and more.
- Platform
- Runs alongside your existing DataWalk deployment.
The DataWalk MCP Server and the governed source give agents governed access, inside your environment.
Go Deeper
What Is An MCP Server?
What the protocol solves, and the governance work it leaves to you. Read more LEARNWhy combine MCP and a Knowledge Graph?
Why neither half work alone Read more LEARNMCP in regulated workflows
Four governance breakpoints to resolve before MCP enters a regulated workflow. Read more BLOGWhy Better Models Cannot Fix Bad Context
Why enterprise AI accuracy depends more on governed context than another model upgrade. Read more Solution BriefDataWalk for Governed Agentic AI
How DataWalk gives agents a maintained, governed knowledge graph of your business. Read more SHEETDataWalk MCP Server
Architecture, capabilities, security controls, deployment requirements, and benchmark results. Read moreMove AI Beyond The Pilot.
Give agents governed access to trusted context, under the user’s own credentials, with the auditability production review expects.
