MCP Server Development

MCP Server Development That Connects Claude to Everything in Your Stack

Anthropic's Model Context Protocol is how Claude accesses your internal tools, databases, and APIs. We design, build, and deploy production MCP servers — so Claude can act on real enterprise data, not just discuss it.

60+
4.9/5
Client satisfaction score
MCP servers deployed
12
Enterprise connectors built
3 days
Avg. time to first working server
100%
Claude-focused practice
MCP
Anthropic's open protocol for AI tool use
SSE + stdio
Both transport layers supported
OAuth 2.0
Enterprise-grade auth on every server
Salesforce, Jira, SAP
Pre-built enterprise connector patterns
What We Deliver

MCP Server Development Built for Enterprise Scale

An MCP server isn't a weekend project when you need it to connect to production CRMs, comply with data residency rules, and handle 500 concurrent Claude users. Here's what we build.

🔌
Internal API Connectors
We build MCP servers that expose your internal REST APIs, GraphQL endpoints, and microservices as tools Claude can call. Your proprietary systems become Claude-accessible without rewriting a single line of existing code.
🗄️
Database Read/Write Servers
PostgreSQL, Snowflake, BigQuery, or Oracle — we build MCP database servers with row-level security, read-only modes for safety, and natural-language query translation. Claude queries your data warehouse in plain English.
☁️
SaaS Platform Integrations
Salesforce CRM, Jira project data, SAP ERP records, ServiceNow tickets, HubSpot contacts. We've built MCP layers over every major enterprise SaaS so Claude can read, summarise, and update records without copy-paste.
🔐
Authentication & Governance
Every MCP server we build includes OAuth 2.0 authentication, per-user scoping, and audit logging. Administrators know exactly which users accessed which data through Claude and when — essential for regulated industries.
📁
File & Document Servers
SharePoint, Confluence, Google Drive, Box — we build MCP document servers that let Claude search, read, and summarise internal documents. Combine with AI agent development to build document-processing workflows.
🚀
Remote MCP Deployment
We deploy MCP servers as hosted remote services — running on your cloud infrastructure or ours — so they're available to every Claude user in your organisation without local setup. Works with Claude Cowork and Claude Code enterprise deployments.
What a Production MCP Server Looks Like

Not a Tutorial. A Real Server for Real Enterprise Data.

Most MCP tutorials connect to a weather API. We connect to your Salesforce instance, with field-level security, per-user token scoping, and rate limiting. Here's a simplified view of what that looks like under the hood.

# Salesforce MCP Server — enterprise pattern
@mcp.tool()
async def get_account_summary(account_id: str, user_context: UserContext) -> dict:
    # Per-user Salesforce token (not shared credentials)
    sf = salesforce_client_for_user(user_context.user_id)
    # Field-level security enforced at query time
    account = sf.Account.get(account_id, fields=allowed_fields(user_context.role))
    audit_log(user_context, "read", "Account", account_id)
    return format_account_summary(account)

Read our full MCP Protocol guide for a deep-dive on architecture patterns.

Our Process

How MCP Server Development Works

From API audit to production deployment in a structured engagement. No assumptions about what your stack can handle — we find out first.

01

System Audit & Tool Design

We map every data source and internal API relevant to your Claude use cases. For each source, we design the MCP tool schema — what Claude can ask, what parameters it passes, what it gets back. This is the architecture phase. Getting the tool design wrong means Claude asks the right questions but gets useless answers.

02

Auth & Security Architecture

We design the authentication model before writing a single server. For most enterprise deployments, this means per-user OAuth token propagation so Claude acts with the requesting user's permissions — never a shared service account. We also define rate limits, field-level exclusions, and audit log schema.

03

Server Build & Integration Testing

We build in Python (FastMCP or raw MCP SDK) or TypeScript, depending on your team's stack. Each MCP server is integration-tested against real sandbox instances of your systems — not mocked data. We validate Claude's actual tool-calling behaviour against the server before deployment.

04

Enterprise Deployment & Monitoring

We deploy servers to your infrastructure (AWS, Azure, or GCP) as containerised services with health checks, structured logging, and alerting. For Cowork environments, we configure remote MCP endpoints. For developer deployments, we set up the server registry and CLAUDE.md instructions. We hand over full documentation and runbooks.

05

Ongoing Support & Expansion

Your MCP server estate should grow as your Claude use cases grow. We offer retainer-based support to add new tools, update schemas as APIs change, and expand to new data sources. Many clients start with one Salesforce server and end up with twelve servers covering their entire enterprise data layer.

Who This Is For

MCP Server Development Is Right for Your Organisation If...

The MCP layer is where Claude stops being a smart assistant and starts being a productive operator of your enterprise systems.

Engineering Leaders

You've tried the Anthropic MCP quickstart and hit a wall

The tutorial gets you to "Hello, world" over stdio. Your production requirements — per-user OAuth, role-based field exclusions, connection pooling, audit logging — are a different challenge. We've solved these patterns across dozens of enterprise deployments.

CIOs / CTOs

You want Claude to act on data, not just talk about data

Your knowledge workers want to ask Claude "what's the status of the Goldman Sachs renewal?" and get a live Salesforce answer — not a general lecture on CRM. MCP is the bridge. Without it, Claude is limited to documents it's already seen. With it, Claude becomes a real-time operator of your enterprise stack.

AI/ML Platform Teams

You're building an internal AI platform on Claude

If you're building a centralised Claude Enterprise implementation that multiple teams will use, you need a robust MCP server registry. We build the foundation — auth framework, deployment patterns, documentation standards — that lets your teams add new servers safely.

60+
Production MCP servers built
8
Industries served including FSI & healthcare
4.9/5
Client satisfaction across engagements
Claude Partner
Anthropic Partner Network certified
Related Services

MCP Servers Work Best in Context

MCP development is most powerful when combined with the right deployment infrastructure and agent architecture.

Ready to Connect Claude to Your Systems?

Your Data Isn't Useful to Claude Until You Build the Bridge.

MCP server development is a specialised discipline. The difference between a server that works in a demo and one that runs in production for 500 users is architecture, security, and experience. Book a free strategy call with our certified architects.

FAQ

Frequently Asked Questions About MCP Server Development

What is the Model Context Protocol (MCP) and why does it matter?
MCP is Anthropic's open protocol that standardises how AI models like Claude connect to external tools and data sources. Before MCP, every integration required custom prompt injection or bespoke API wrappers. MCP gives Claude a standard interface to call tools, read resources, and receive structured responses — making integrations reusable, secure, and manageable at scale. Read our complete MCP Protocol guide for a deep-dive.
Do you build MCP servers for both Claude.ai (Cowork) and Claude Code / API?
Yes. Remote MCP servers using the SSE transport can be registered directly in Claude Cowork, making them available to all knowledge workers in your organisation without any local setup. Stdio-based servers are appropriate for developer environments and Claude Code enterprise deployments. We build for both contexts and often both simultaneously.
How do you handle security when Claude has access to our production databases?
Every MCP server we build uses per-user OAuth token propagation — Claude acts with the requesting user's credentials and permissions, never a shared service account. We implement field-level exclusions for sensitive columns, row-level security for multi-tenant data, read-only modes where write access isn't required, and structured audit logging for every tool invocation. Our Claude security and governance service can extend these controls across your full Claude deployment.
How long does MCP server development take?
A single MCP server against a well-documented API typically takes 3–5 business days from kickoff to a working test deployment. Complex servers connecting to multiple data sources, with custom auth flows and governance requirements, typically take 2–4 weeks. Full enterprise MCP registry buildouts across 5–10 systems are typically scoped as 6–12 week engagements.
Can we maintain MCP servers ourselves after you build them?
Yes. We document every server thoroughly and provide handover training for your engineering team. We also offer retainer-based support if you'd prefer us to manage updates, schema changes, and new tool additions on an ongoing basis. Most enterprise clients use a hybrid model: in-house maintenance for simple servers, us for complex governance and new connector development.
What programming languages do you build MCP servers in?
We primarily build in Python using the official MCP SDK and FastMCP framework, and in TypeScript for teams with Node.js infrastructure preferences. We'll match your team's existing language stack where practical. All servers are containerised with Docker for consistency across development, staging, and production environments.