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The Nash MCP server lets an AI agent work with your deliveries directly — look up live status, create orders, request refunds — through the Model Context Protocol, the open standard for connecting AI agents to external tools. Point a Claude, Cursor, or any MCP-capable agent at the server and the Nash platform becomes part of its toolset.
Access to the Nash MCP server is enabled per account. Reach out to sales@usenash.com to get started.

When to use this

Use the MCP server when an AI agent — yours or an off-the-shelf assistant — should operate deliveries as part of a conversation or workflow, rather than your code calling the REST API directly:
  • A customer-facing assistant that creates a delivery when an order is placed, answers “where’s my order?” with live data, and handles refund requests in the same conversation.
  • An internal operations agent that monitors delivery performance, watches courier activity, and runs bulk operations across store locations.
  • An AI workflow that needs delivery as one step among many — quoting, dispatching, and tracking without leaving the agent’s context.
If you’re integrating from application code rather than an agent, the REST API is the more direct path. And if you want an agent that’s already wired into Nash, Nash Agent ships with all of this built in.

What the server exposes

The MCP server surfaces the platform’s core operations as tools your agent can call:
  • Deliveries — create deliveries with pickup and dropoff locations, track status in real time, and request refunds for failed or problematic ones.
  • Couriers — courier information, including location and contact details.
  • Scheduling — delivery windows, including capacity-aware booking.
  • Batch operations — act on multiple deliveries in one call.
  • Store locations — manage delivery origins.
  • Documents — retrieve proof of delivery and related documents.
Tools run with the permissions of the API credentials behind them, so an agent can only see and do what its key allows.

Getting started

Email sales@usenash.com and our team will set up access to the MCP server, configure authentication and permissions, share the function-level documentation, and help with integration testing.

Using LLMs with the Nash API

Hand the full API reference to an LLM — llms.txt and the OpenAPI spec.

Nash Agent

The operations copilot that already has these tools — no integration required.