Enterprise MCP Server Development that goes live in four weeks
Trusted MCP and AI systems partner for startups to enterprise leaders
How you can use GoML's MCP server development services
From a single tool integration to a governed server that powers an entire agent platform, GoML delivers the full MCP development.
Custom MCP server development
Servers that expose your tools, resources and prompts to any MCP client, designed around your workflows and data model.
Enterprise system integration
Secure connections to databases, warehouses (Snowflake), SaaS platforms (Salesforce, Jira, ServiceNow) and internal APIs.
Security, auth & governance
Scoped OAuth, secrets management and audit logging, with a read-only-first model and human-in-the-loop approval before any high-risk action.
AWS deployment & hosting
Containerised, VPC-isolated and autoscaling on Amazon Bedrock, ECS and Lambda, inside your own cloud boundary.
Agent & client integration
Your MCP server wired to Claude, OpenAI, Amazon Bedrock agents and internal copilots, tested against real systems.
Observability & maintenance
Tool accuracy, schema validity, latency, availability and abuse signals tracked continuously, with versioning and ongoing tool additions.
A governed MCP core, developed from proven components
The architecture separates identity, scoped data access, MCP delivery and policy, so AI clients receive only approved, minimized data and never see passwords, secrets or unrestricted records.
MCP gateway
Authenticates and routes MCP tool requests, enforces customer-approved scopes, and applies rate and response policies.
Consent & identity
Connects your identity provider to allowed data scopes, with explicit grant, revocation and short-lived tokens.
Data tool layer
Normalizes your APIs into stable, read-only tools with consistent request and response schemas.
Response policy service
Validates parameters and output schemas, blocks sensitive fields, and attaches source, timestamp and freshness metadata to every response.
Evaluation & telemetry
Tracks tool accuracy, schema validity, latency, availability and abuse signals without storing unnecessary sensitive data.
Deployment & runtime
Containerised and VPC-isolated on AWS, with monitoring, rollback and tenant isolation included.
Every MCP server includes a documented tool catalogue. Each tool has a clear purpose, a defined scope, a stable response schema and an example output, so your team knows exactly what an agent can and cannot do.
Is GoML the right MCP server development partner for you?
AWS Gen AI Partner
Bedrock-native development and access to AWS funding for qualifying pilots and production programmes.
Regulated-industry depth
Healthcare, Life Sciences and Financial Services governance embedded, with PHI isolation, access control and full audit trails.
Production-grade, not prototypes
Security, testing, observability and rollback designed in from the first commit, not bolted on later.
Live in four weeks
A working, governed MCP server delivered in a focused four-week engagement on your AWS environment.
The GoML MCP server development delivery framework
A governed path from your systems to a production MCP server your agents can trust. Each week ends with a client-ready review, with security and observability embedded throughout.
Scope
Map the systems, tools, actions and security requirements the agent must satisfy.
Design
Define the MCP server architecture, authentication model and tool schemas.
Develop
Implement tools, resources, prompts and guardrails against your real data.
Integrate
Connect the server to Claude, OpenAI and agents and test end-to-end on live systems.
Validate
Run security and red-team checks, then client UAT through to formal sign-off.
Operate
Deploy to AWS, observe tool usage, and add new tools over time.
Every engagement delivers a complete MCP package
Design & threat model
Solution design, connection and authorization journeys, a data-flow diagram and a threat model.
The MCP connector
A provider-neutral MCP server with read-only tools, consent, audit, rate limits and secret management.
Security & schema pack
A security control matrix, scope policy, response schemas with source and freshness metadata, and a security evaluation set with test results.
Launch package
Pilot analytics, a deployment package, an operating runbook and a handover workshop.
Clear, measurable acceptance criteria
Every engagement is accepted against explicit standards agreed up front, so success is measured, not assumed.
100% of out-of-scope requests denied
No Severity 1 or 2 defects at sign-off
Source & freshness metadata on every response
High tool-call success, verified on your data
Where enterprises use GoML-developed MCP servers
Financial data agents
Natural-language querying of Snowflake and data warehouses with auditing and PII controls.
Clinical & healthcare copilots
Governed access to clinical systems and documents using zero-PHI-exposure patterns.
Internal knowledge copilots
Jira, Confluence, SharePoint and document stores exposed safely to agents.
Ops & DevOps agents
Cloud, CI/CD and ticketing actions with human-in-the-loop for destructive steps.
Customer-facing assistants
Product, order and account systems connected to conversational agents.
Data & BI assistants
Dashboards and metrics linked back to source data for explainable answers.
MCP server development success stories
Paramean: AI financial assistant for value-based care settlements
GoML developed an AI financial assistant embedded in Paramean's settlement module. It uses Model Context Protocol (MCP) for authenticated, client-isolated access to Snowflake data and contract documents. It runs on Amazon Bedrock with Claude, with complete auditability and zero PHI exposure.
The Connecter: DeFi yield-farming agents
A multi-agent assistant on Amazon Bedrock AgentCore that executes swaps, approvals and deposits through tool calls.
Read the case study →SaluberMD: agentic remote diagnostics
An agentic diagnostics pipeline integrated securely via APIs into an existing telemedicine backend, HIPAA- and GDPR-compliant on AWS.
Read the case study →FAQs on MCP server development
What is an MCP server?
The Model Context Protocol (MCP) is the open standard for connecting AI models and agents to the systems, data and tools they need to do real work. An MCP server is the component that exposes those tools, resources and actions to any MCP-compatible client, such as Claude, an OpenAI client or an agent running on Amazon Bedrock.
What is MCP server development?
MCP server development is the work of developing that server for your enterprise: defining which tools and data an agent can reach, wiring it securely to your databases, SaaS applications and internal APIs, and enforcing authentication, scoping and audit around every call. You develop one governed MCP server that every agent and model can use, rather than maintaining brittle, bespoke integrations for each new AI use case.
The result is a provider-neutral layer that works with Claude, OpenAI and any other MCP-compatible client, so you are never coupled to a single model provider. GoML develops these servers as production systems, not prototypes: authenticated, client-isolated, observable and deployed inside your AWS environment.
Why develop an MCP server instead of custom integrations?
A custom integration ties one agent to one system. An MCP server is developed once and reused by every MCP-compatible agent and model, with a single governed layer for authentication, scoping and audit, so you avoid recreating and re-securing integrations for each new AI use case.
Do we get locked into one AI provider?
No. GoML develops a provider-neutral MCP layer, so one server works with Claude, OpenAI and any other MCP-compatible client, without coupling you to a single model provider.
Is MCP secure enough for regulated or enterprise data?
Yes, when developed correctly. GoML implements scoped OAuth, MCP authentication, client-specific data isolation, secrets management, complete audit trails, a read-only-first rollout that exposes write or high-risk tools only through change control, and human-in-the-loop approval for high-risk actions, all deployed inside your own AWS environment.
Which systems can an MCP server connect to?
Databases and data warehouses (including Snowflake), SaaS platforms such as Salesforce, Jira and ServiceNow, internal APIs, document and knowledge stores, and cloud and DevOps tooling. Any system with an API can be exposed as governed MCP tools.
Do you develop MCP servers on AWS and Amazon Bedrock?
Yes. As an AWS Gen AI Partner, GoML develops MCP servers to run natively on Amazon Bedrock, ECS and Lambda, VPC-isolated inside your account, with access to AWS funding for qualifying pilots.
How long does MCP server development take?
GoML delivers a working, governed MCP server in a focused four-week engagement, then supports ongoing tool additions and maintenance as your agent estate grows.
Do you maintain the MCP server after launch?
Yes. Engagements include observability, versioning, monitoring and the option of ongoing support to add tools and adapt the server as your systems and use cases evolve.
