Capability
System Integration
MCP servers that connect AI to existing tools: CRM, databases, APIs. One universal interface, compatible with every major AI client.
Overview
Model Context Protocol (MCP) lets a single server expose internal APIs, databases, and SaaS tools to any compatible AI client through a universal interface. The AI discovers what's available at runtime, reads live data, and acts on it. One implementation covers Claude Desktop, ChatGPT, Cursor, and custom applications. The result is AI that actually operates within business systems instead of just generating text about them.
How It Works
Custom MCP Servers
Servers that expose APIs, databases, and SaaS tools as typed definitions with schema validation. The AI reads from a CRM, writes to a project tracker, or queries a data warehouse through a standardized interface.
Local & Remote Deployment
Runs locally on a developer's machine or deployed as a remote service. Stateful sessions let the AI discover capabilities at connection time and maintain context throughout a conversation.
Workflow Chaining
The AI chains multiple tools in a single conversation: query a database, process results, update a CRM, send a notification. Complex multi-step workflows without custom orchestration code.
Security & Access Control
Per-tool and per-user permission scoping. Audit logging on every invocation, rate limiting, and sandboxed execution.