MCP Server Development Services

Let Assistants Act on Your Systems, With Guardrails

When AI needs to open a ticket, look up an order, or draft an update in your CMS, those actions should run through tools your security team can scope, log, and revoke.

We build Model Context Protocol servers that wrap the APIs and data you already own, so assistants get reliable capabilities without a one-off integration for every new model.

We start with a narrow set of high-value tools, then expand once permissions, observability, and human review prove the pattern is safe to grow.

Share Your Goals See Results

MCP and AI Tool Programs

FarmscapeBest practicesavailable via chat in the field.Crews needed best-practice answers in the field without opening a web service manual dozens of pages long. We imported Farmscape's service manuals into a searchable knowledge base, exposed them through an MCP server, and deployed a chat assistant in Google Workspace so staff get grounded answers in company-wide chat.

AskEmployee question in Google Chat

Find manualsSearch indexed service docs

MCP toolsSearch and document lookup

Grounded answerReply with source path

View case study CPESRHours saveddaily on routine customer support.Course subscribers often ask questions he had already answered by email. The system drafts customer email and internal Q&A answers from those prior replies and course material, with staff review before anything goes out, saving hours daily on routine questions.

AskInbox email or staff question

Find contextPast replies and course material

DraftAI prepares a reply

Staff reviewEdit, approve, send

View case study

Endertech operationsOne platformfor CRM, proposals, projects, tickets, time, and invoicingWe run Endertech on Ansible, our own platform: CRM and deals, AI-drafted proposals, projects and sprints, email-to-ticket support with AI assist, time tracking to QuickBooks invoicing, and a knowledge base.

CRMContacts and deals

ProposalsAI-assisted drafts

Projects and ticketsSprints and support requests

Time and invoicingTracked time becomes invoices

What an MCP Server Lets AI Do for Your Business

Assistants stop at advice when they cannot call your systems safely. MCP tools turn approved actions into repeatable steps with sign-in, scopes, and logs.

Look up live records

Orders, tickets, and account context return from the systems your team already trusts, not from stale exports.

Draft updates for review

AI prepares CRM notes, CMS drafts, or support replies, and people approve before anything customer-facing ships.

Run scoped actions

Create tasks, route work, or enqueue jobs through tools with explicit limits, rate limits, and audit trails.

Tool Contracts, Permissions, and Operations

We narrow initial tools to high-value actions, then expand with telemetry that proves safety.

Use case and policy

Allowed actions, data classes, and human-in-the-loop triggers documented before code ships.

Tool contracts

Schemas, examples, and validation so models call the right tool with stable arguments.

Implement and observe

Auth, rate limits, structured errors, metrics, and tracing per tool invocation.

Where MCP Sits in Your AI Stack

AI agent orchestration

Multi-step workflows that combine tools, retrieval, and human review.

RAG development

Document retrieval alongside transactional tools when answers must cite sources.

API and integration layer

OpenAPI-first services that feed both people and assistants.

You can count on us.

Firm Price
The price we quote for a scope of work is the price you pay. No surprises.
Detailed Plan
Visual and written plans make clear the scope of work and guide the project to success.
Steady Cadence
Progress and working decisions arrive on an agreed, dependable rhythm.
Prompt Communication
Questions and issues are acknowledged promptly, with clear ownership and next steps.

Frequently Asked Questions

What is an MCP server?

A Model Context Protocol (MCP) server exposes scoped tools and data to AI assistants through a standard contract. Instead of custom glue for every assistant, your team defines which actions are allowed, how they authenticate, and what gets logged when a model calls a tool.

How is MCP different from an API?

Your business APIs stay the source of truth. MCP sits in front of them with tool definitions, examples, and guardrails tuned for model use. Assistants discover capabilities consistently, and operators can version or retire tools without rewriting every integration.

Which systems can it connect?

Any system you can reach with a supported API or database connection: CRM, commerce, ticketing, CMS, email, Slack or Teams, ERP, and internal databases. We narrow initial tools to high-value, low-risk actions, then expand once telemetry shows safe behavior.

How do sign-in and permissions work?

Tools run under service accounts or per-user OAuth, depending on policy. Each session carries scopes that limit which records or actions are available, and structured logs capture who invoked which tool with what result. Sensitive actions can require confirmation or human approval in your application layer.

Can we move existing integrations to MCP?

Often yes. If you already have REST or GraphQL services, we can wrap them as MCP tools with clearer schemas and centralized auth. The goal is not to replace working APIs, but to give assistants one governed surface instead of ad hoc scripts per use case.

How do we start?

Share the systems, policies, and allowed actions you want assistants to perform. We map one or two tools against staging data, prove logging and permissions, then harden for production and expand the toolkit with your security and operations teams involved.