MCP Server Development

Give AI the Tools to Act

Model Context Protocol servers that connect AI assistants to business systems through safe tools, clear auth, observability, and governance your team can operate.

Discuss MCP Development See MCP & AI Integration Work

When MCP Work Fits

When assistants need governed actions on your data, not copy-paste.

Generic LLM chat can't open tickets, query orders, or update records without well-defined tools, permissions, and audit trails.

Ad hoc RAG isn't enough

Agents need transactional tools with guardrails alongside document search.

Security and tenancy

Each tool call must respect roles, scopes, and PII policy.

API sprawl behind the model

Normalize messy backends into coherent MCP resources.

Reliability under real use

Timeouts, retries, and user-visible errors need design.

Evaluation & drift

You need to know when tool behavior or data quality regresses.

Operational ownership

Someone must run, version, and patch MCP deployments.

Production Mindset

Agents wired like services, not demos.

We bring API integration discipline, auth patterns, and logging culture from years of shipping business systems before assistants became the interface.

Established Technical Partner

Two-plus decades shipping web platforms across industries and stacks.

Senior-Led Delivery

Engineering and architecture leads stay on the project after the pitch.

One Accountable Team

Strategy, design, engineering, and support work from the same plan.

How We Build MCP

Threat model, tool design, ship, observe.

We narrow initial tools to high-value, low-risk actions, then expand with telemetry proving safety.

Use case & policy

Allowed actions, data classes, and human-in-the-loop triggers.

Tool contracts

Schemas, examples, and validation for stable model behavior.

Implement & harden

MCP server, auth, rate limits, and structured errors.

Operate

Metrics, tracing, and versioned rollouts.

Relevant Work

AI tool and MCP programs.

AI tool and integration builds selected for real production use, policy compliance, and measurable team impact.

Furniture Retail - Ecommerce

Today’s Patio: Shopify + STORIS Integration with AI Search & Offline Conversion Tracking

Endertech helped Today’s Patio move from WooCommerce to Shopify, integrate their STORIS ERP, re-architect a complex catalog, and layer on conversational search and offline conversion tracking—creating a scalable ecommerce and marketing foundation that continues to support strong online growth.

View case study

Stack

Language-agnostic MCP with your existing services.

TypeScript, Python, or Go workers, based on your ops and latency needs.

MCP protocol

Resources, tools, and prompts with clear capability boundaries.

Identity & auth

OAuth, service accounts, and per-session scoping.

Connectors

CRM, commerce, ticketing, and internal databases via owned APIs.

Observability

Structured logs and traces per tool invocation.

Safety patterns

Confirmation steps, dry-run modes, and kill switches.

Deployment

Containers, serverless, or VPC patterns sized to your security team.

Ways to Work Together

Prototype, MVP server, or platform program.

Start with a focused feasibility spike or go straight to a production roadmap, scoped to your team's readiness and compliance posture.

Feasibility spike

Prove one tool against staging data with evaluation harness.

MVP MCP server

Production-hardened initial toolkit with docs.

Agent platform layer

Shared auth, registry, and governance across teams.

Ongoing iteration

Monthly capacity for new tools and model upgrades.

Start With the Problem

Exploring MCP for your internal or customer assistants?

Start with the systems, policies, and allowed actions. We'll help you scope tools that ship safely.

Discuss MCP Development See MCP & AI Integration Work

MCP Server Development

Give AI the Tools to Act

Model Context Protocol servers that connect AI assistants to business systems through safe tools, clear auth, observability, and governance your team can operate.

Discuss MCP Development See MCP & AI Integration Work

When MCP Work Fits

When assistants need governed actions on your data, not copy-paste.

Generic LLM chat can't open tickets, query orders, or update records without well-defined tools, permissions, and audit trails.

Ad hoc RAG isn't enough

Agents need transactional tools with guardrails alongside document search.

Security and tenancy

Each tool call must respect roles, scopes, and PII policy.

API sprawl behind the model

Normalize messy backends into coherent MCP resources.

Reliability under real use

Timeouts, retries, and user-visible errors need design.

Evaluation & drift

You need to know when tool behavior or data quality regresses.

Operational ownership

Someone must run, version, and patch MCP deployments.

Production Mindset

Agents wired like services, not demos.

We bring API integration discipline, auth patterns, and logging culture from years of shipping business systems before assistants became the interface.

Established Technical Partner

Two-plus decades shipping web platforms across industries and stacks.

Senior-Led Delivery

Engineering and architecture leads stay on the project after the pitch.

One Accountable Team

Strategy, design, engineering, and support work from the same plan.

How We Build MCP

Threat model, tool design, ship, observe.

We narrow initial tools to high-value, low-risk actions, then expand with telemetry proving safety.

Use case & policy

Allowed actions, data classes, and human-in-the-loop triggers.

Tool contracts

Schemas, examples, and validation for stable model behavior.

Implement & harden

MCP server, auth, rate limits, and structured errors.

Operate

Metrics, tracing, and versioned rollouts.

Relevant Work

AI tool and MCP programs.

AI tool and integration builds selected for real production use, policy compliance, and measurable team impact.

Furniture Retail - Ecommerce

Today’s Patio: Shopify + STORIS Integration with AI Search & Offline Conversion Tracking

View case study

Stack

Language-agnostic MCP with your existing services.

TypeScript, Python, or Go workers, based on your ops and latency needs.

MCP protocol

Resources, tools, and prompts with clear capability boundaries.

Identity & auth

OAuth, service accounts, and per-session scoping.

Connectors

CRM, commerce, ticketing, and internal databases via owned APIs.

Observability

Structured logs and traces per tool invocation.

Safety patterns

Confirmation steps, dry-run modes, and kill switches.

Deployment

Containers, serverless, or VPC patterns sized to your security team.

Ways to Work Together

Prototype, MVP server, or platform program.

Start with a focused feasibility spike or go straight to a production roadmap, scoped to your team's readiness and compliance posture.

Feasibility spike

Prove one tool against staging data with evaluation harness.

MVP MCP server

Production-hardened initial toolkit with docs.

Agent platform layer

Shared auth, registry, and governance across teams.

Ongoing iteration

Monthly capacity for new tools and model upgrades.

Start With the Problem

Exploring MCP for your internal or customer assistants?

Start with the systems, policies, and allowed actions. We'll help you scope tools that ship safely.

Discuss MCP Development See MCP & AI Integration Work