0-4 yrs
0-4 yrs
20%
20%
5
5
100+
100+
MCP SERVER DEVELOPMENT
MCP server development covers a range of work depending on what you're connecting and why. Some projects are straightforward: expose a database to Claude or ChatGPT or any other AI tool, so your team can query it in natural language. Others are more involved: build an agent that can read your CRM, check inventory, draft an email, and file a support ticket, all through MCP tools.
MCP Solutions
MCP isn't one thing. It's a protocol, and the server you build depends on what you need the AI to do. A server that exposes read-only data (an MCP resource) is different from one that lets the AI take actions (MCP tools). We build both. Here's how the work breaks down:
Custom MCP Server Development
We build MCP servers tailored to your business. That includes defining the tools the AI can call, the resources it can read, the prompts it can use, and the authentication that controls access. Every server is built for your specific use case, not a generic template.
MCP Integration Services
Connecting MCP servers to your existing stack. CRMs, ERPs, databases, internal APIs, third-party services. We handle the plumbing so your AI model can pull data from and push actions to the tools your team already uses.
MCP Server Maintenance and Upgrades
MCP is a moving target. The protocol is evolving, new transports are being added, and AI clients update their MCP support regularly. We keep your MCP servers current with protocol changes, fix issues, and add new tools as your needs grow.
MCP Consulting
Not sure if MCP is right for your use case? We'll evaluate it. Sometimes a direct API integration is simpler and better. Sometimes MCP is the right abstraction because you want multiple AI models to access the same tools. We'll tell you which approach fits before you commit to building.
MCP IN PRACTICE
What an MCP Server Actually Does
01 / CUSTOMER DATA
lookup_customer
Takes a customer email, queries your database, and returns their account details, subscription tier, and last 5 orders.
02 / SUPPORT HISTORY
get_open_tickets
Takes a customer ID, pulls their open support tickets from your helpdesk system, and returns ticket status and history.
03 / READY TO REVIEW
draft_response
Takes the customer context and the current question, then generates a response draft that your support agent can review and send.
When your support agent asks Claude, it calls lookup_customer, gets the order details, and gives a complete answer. No tab-switching. No copy-pasting. The agent stays in one place.
UNDER THE HOOD
How an MCP Server Connects to Your Systems
Your Team
Claude Desktop / Claude Code / Custom AI Client
MCP Protocol · JSON-RPC over stdio or HTTP+SSE
Your MCP Server (Ruby)
PostgreSQL
Your data
Internal APIs
Your tools
Third-party Services
Stripe, HubSpot, etc.
Transport options
stdio · For local use
The AI client launches the MCP server as a subprocess. Fast, no network setup, good for developer tools and local workflows.
HTTP with SSE · For remote access
SSE (Server-Sent Events) lets AI clients connect over HTTPS while the MCP server runs on your infrastructure. Supports multiple concurrent users and works across networks.
YOUR SYSTEMS, CONNECTED
What You Can Connect Through MCP
Databases
PostgreSQL, MySQL, MongoDB. Let Claude query your data in natural language. We build read-only or read-write tools depending on your comfort level.
Internal APIs
Your existing REST or GraphQL APIs wrapped as MCP tools. The AI calls them the same way your front-end does, but through the MCP server’s access controls.
CRMs and Helpdesks
HubSpot, Salesforce, Zendesk, Freshdesk. Look up customer records, create tickets, update deal stages. Your sales and support teams get AI that actually knows your customers.
Payment and Billing
Stripe, Razorpay, your custom billing system. Check payment status, look up invoices, handle subscription queries. Read-only by default for obvious reasons.
File Systems and Documents
Let Claude read your internal docs, SOPs, or knowledge base. Useful for onboarding tools and internal support bots that need company-specific information.
Monitoring and DevOps
Server metrics, error logs, deployment status. Build an MCP server that lets Claude check if your production systems are healthy and summarize recent incidents.
BUILT FOR PRODUCTION
Our MCP Development Stack
01 / LANGUAGE
Ruby
We use the official MCP Ruby SDK when it fits, and build custom transport layers when it doesn’t. Ruby handles JSON-RPC cleanly and integrates naturally with Rails applications.
02 / DATABASE
PostgreSQL
PostgreSQL for any data the MCP server needs to persist: tool call logs, session state, and cached responses.
03 / BACKGROUND PROCESSING
Sidekiq with Redis
Some MCP tools trigger operations that take more than a few seconds, like generating reports or processing bulk data. These run in background jobs so the AI client doesn’t time out.
04 / AUTHENTICATION
Token-based access controls
Token-based auth for HTTP transport. We implement per-user and per-tool access controls so you can give different teams access to different MCP capabilities.
05 / TESTING
Automated tool testing
Every MCP tool gets automated tests that verify input validation, output format, error handling, and authorization. We test against Claude Desktop and Claude Code before deployment.
06 / DEPLOYMENT
Docker with CI/CD
Docker containers with CI/CD. Your MCP server deploys the same way as any other backend service. No special infrastructure required.
FURTHER READING
We wrote a technical deep dive on MCP server architecture and how it fits into Ruby on Rails applications:
faqs
Everything you need to know before getting started with us. Below are out most common questions we get asked.
What is an MCP server?
MCP stands for Model Context Protocol. It's an open standard created by Anthropic that defines how AI models connect to external tools and data sources. An MCP server is a program that exposes your tools, databases, or APIs to AI models through this protocol. When Claude or another AI client connects to your MCP server, it can read your data (resources), call your functions (tools), and use predefined workflows (prompts). Think of it as a standardized way to give AI access to your systems without building custom integrations for every model.
What does MCP server development involve?
MCP server development means building the server that sits between your systems and the AI. The work includes defining which tools the AI can call and what parameters they accept, setting up resources the AI can read, configuring the transport layer (stdio for local use, HTTP with SSE for remote access), handling authentication and authorization, and testing the server against AI clients like Claude Desktop or Claude Code. The scope depends on what you're connecting. A server that exposes a single database is simpler than one that orchestrates actions across multiple internal systems.
How much does custom MCP server development cost?
Cost scales with complexity. An MCP server that wraps a single API or database with a handful of tools is a smaller project than one that connects to multiple internal systems, handles complex authorization rules, and supports concurrent users. We don't quote without understanding your systems and use cases first. What we can say is that MCP servers are backend services, so the ongoing cost is hosting and maintenance, not per-query licensing fees.
What tools and languages do you use to build MCP servers?
We build MCP servers in Ruby. The MCP protocol uses JSON-RPC over standard transports, which Ruby handles well. For the rest of the stack: PostgreSQL for any data persistence, Redis for caching and session management, and Sidekiq for background jobs if the MCP tools trigger long-running operations. We deploy on Docker with CI/CD pipelines. If your existing application is Ruby on Rails, the MCP server integrates naturally with your codebase. If your stack is something else, the MCP server runs as a standalone service that communicates over HTTP.
Can MCP servers work with AI models other than Claude?
Yes. MCP is an open protocol. While Anthropic created it and Claude has native MCP support, any AI client that implements the MCP specification can connect to your server. The protocol is gaining adoption across the AI ecosystem. Building on MCP means your tools and data become accessible to current and future AI models without rebuilding the integration layer for each one.
What's the difference between MCP tools, resources, and prompts?
Tools are functions the AI can call to take actions: send an email, create a record, run a query. The AI decides when to call them based on the user's request. Resources are data the AI can read: a file, a database record, a live dashboard metric. They provide context without the AI needing to take action. Prompts are predefined templates that guide how the AI uses your tools and resources for specific workflows. A well-built MCP server uses all three to give the AI the right mix of information and capabilities.
How do you secure an MCP server?
Authentication and authorization are built into every MCP server we deliver. That means controlling which users and AI clients can connect, which tools they can call, and what data they can access. For servers exposed over HTTP, we implement token-based authentication, TLS encryption, and rate limiting. For tools that modify data (create, update, delete), we add confirmation steps so the AI can't take destructive actions without human approval. Audit logging tracks every tool call so you have a record of what the AI did and when.
Why hire a development company for MCP server work instead of building in-house?
MCP is new. Most development teams haven't built an MCP server before. The protocol documentation is evolving, transport implementations have edge cases, and getting tool definitions right so the AI actually calls them correctly takes iteration. A team that's already shipped MCP servers in production can save you the trial-and-error phase. We've built MCP integrations that connect to databases, CRMs, internal APIs, and third-party services. That experience means your server works correctly the first time instead of after weeks of debugging protocol quirks.