Enterprise MCP Access For AI Agents | Nexla

MCP Server & Gateway

The Governed 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.

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.

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.

Interactive explorer of the six MCP security and governance layers Nexla enforces on every tool call.

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.

01 Identity
02 Auth Key
03 Credential
04 Connector
05 Source Policies
06 User Data

Layer 01

Identity

What it governs

Agent and user authentication.

Enforced on every tool call

How a tool call flows through all six ↗

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

Governed Data Access for Every AI Agent in Your Stack.

Frequently Asked Questions

1. 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.

2. Why Is MCP Important for AI Orchestration?
   MCP standardizes how AI agents access data and tools across systems, enabling seamless multi-agent workflows. Nexla adds orchestration, governance, and runtime execution, plus one MCP endpoint for 1000+ sources and natural-language pipeline building with Express.dev.

3. How does Nexla's MCP server differ from vendor-specific MCP servers?
   Nexla provides unified access to 1000+ data sources through one MCP endpoint, while vendor MCP servers connect to single platforms only. Nexla MCP includes pipeline building via Express MCP, legacy system support without native MCP, enterprise orchestration, and real-time data with sub-5 minute latency across all sources.

4. 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.

5. How does Nexla MCP ensure enterprise-grade security and governance?
   Nexla MCP includes OAuth 2.0 + Keycloak authentication, role-based access control per agent, comprehensive audit logging for every query, rate limiting, HTTPS-only communication, and SOC 2, HIPAA, GDPR compliance readiness. Deploy cloud-hosted, self-hosted in your VPC, or hybrid with sensitive data on-premises.

6. 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.