MCP Server & Gateway

The Governed MCP Gateway Between Your Enterprise Data and Your AI Agents

Nexla MCP Server & Gateway is the policy-enforcing, context-routing layer that connects any enterprise data source to any MCP-compatible AI agent. Every tool call is routed, permissioned, and governed before data reaches the agent.

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Governed Data Flow for AI Agents

How It Fits In The Architecture

Actions and writes flow back through the same path.

The MCP Server & Gateway sits at the delivery point. It receives MCP Tool calls from agents, routes them through the appropriate data pipelines, enforces access policies, and returns governed, context-enriched responses.

Animated pipeline: Sources to Connectors to Probe to Nexsets to Sync API to the MCP Server and Gateway to AI Agents, grouped into Ingest, Discover and govern, and Serve

Three Core Functions

Context

The Gateway connects to Nexla’s Context Engine (Helix), which grounds each MCP tool call in enterprise-specific knowledge: schemas, lineage, prior executions, and business documentation. Agents receive data they can reason over, not just raw records.

Router

The Gateway routes each tool call to the correct Nexset and Sync API endpoint. For cross-system workflows, it orchestrates multiple hops in a single execution, managing auth, rate limits, and retries per system.

Policy

Every tool call passes through the full MCP Security & Governance layer before data is returned.

MCP Security & Governance

Every Tool Call Passes Through Every Layer

Six layers are enforced at the gateway before data reaches an agent. Select a layer to see what it controls.

Enforced on every tool call

Layer 01 of 06

Identity

What it governs

Agent and user authentication.

From Data To MCP Tools

MCP Tool Creation Flow

Every MCP tool available through the Gateway is created from a governed Nexset via Sync API:

Connector

Ingests data from a source system (1000+ supported)

Agentic Probe

Discovers and profiles the source

Data Product (Nexset)

Is created as a governed virtual data product (schema, docs, access control)

Sync API

Exposes the Nexset as a Data API (GET /data) or API Service (POST /action)

MCP Gateway

Publishes the API as an MCP Tool or MCP Action, discoverable by agents

Delivered Value

What Agents Get

Any MCP-compatible agent or orchestrator connecting through the Nexla MCP Gateway receives:

MCP Tools sourced from 1000+ enterprise data systems

Schema-aware, semantically enriched data (not raw column names)

Context-grounded responses via the Helix Context Engine

Governed read and write access with full audit trail

Cross-system orchestration in a single tool call

Compatible with LangChain, LangGraph, CrewAI, AutoGen, Anthropic Claude (native MCP), and any framework implementing the open MCP specification.

Governance By Design

Security & Governance

Nexla is SOC 2 Type II certified. The MCP Gateway enforces governance at every layer:

RBAC at dataset, row, and column level
Field masking for PII and sensitive columns
Full audit log: every tool call logged with agent identity, timestamp, and query
End-to-end data lineage for all data accessed via MCP
VPC and on-premise deployment options for sensitive environments

MCP Architecture

technical deep-dive

Nexsets

the data products the Gateway serves

Converged Integraton

how data reaches Nexsets

Data Security

governance detail

Frequently Asked Questions

What is Model Context Protocol (MCP) and why does it matter for AI agents?

MCP (Model Context Protocol) is a standardized way to connect AI agents like ChatGPT, Claude, and Copilot to external data sources, tools, and workflows. It enables AI agents to access enterprise data, execute tasks, and provide personalized insights without custom API integrations for each connection.

Why is MCP important for AI orchestration?

MCP standardizes how AI agents access data and tools across systems, enabling multi-agent workflows. Nexla adds the governance MCP lacks: every tool call is grounded in Helix context, permissioned by policy, and logged. Agents get task-specific tools from 1,000+ systems, and teams build pipelines in natural language with Express.dev.

How does Nexla's MCP server differ from vendor-specific MCP servers?

Vendor MCP servers expose every tool for a single app with no business context. Nexla serves governed, task-specific tools from 1,000+ systems, grounded in Helix context and enforced by a six-layer security stack. In Nexla benchmarks, task-specific servers used up to 32.7x fewer tokens and 4.7x fewer tool calls, with equal or better accuracy.

What is Express MCP and how does it enable AI agents to build data pipelines?

Express MCP is the only MCP server that lets AI agents BUILD data pipelines, not just query data. Using natural language commands like “Connect Salesforce to Snowflake and sync hourly,” AI agents create production pipelines with automatic schema mapping, transformations, and governance. Available now in ChatGPT GPT Store.

How does Nexla MCP ensure enterprise-grade security and governance?

Every tool call passes a six-layer security and governance stack, starting with verified identity (OAuth 2.0 and Keycloak). Controls include RBAC at dataset, row, and column level, PII masking, rate limiting, HTTPS-only traffic, and a full audit log. Nexla is SOC 2 Type II, ISO 27001, HIPAA, GDPR, and CCPA compliant, with cloud, VPC, on-premises, or hybrid deployment.

Can Nexla MCP connect AI agents to legacy systems without native MCP support?

Yes, Nexla MCP dynamically creates MCP endpoints for ANY system, including SAP, Siebel, mainframes, and proprietary databases, even when those systems lack native MCP support. This enables AI agents to access legacy enterprise data through standardized MCP protocol with full governance and audit trails.