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MCP Development

AIinfrastructurethatpowers

Build the AI infrastructure that powers next-generation applications. Custom MCP servers, tools, and integrations.

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MCP Servers Built
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Tools Developed
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Faster Development

MCP Server Example

Build powerful AI tool servers with clean, type-safe code.

MCP Server

~16 lines
style ="color: #ff7b72;">from mcp.server style ="color: #ff7b72;">import Server
style ="color: #ff7b72;">from mcp.types style ="color: #ff7b72;">import Tool, TextContent

server = style ="color: #d2a8ff;">Server(style ="color: style ="color: #6b7280;">#a5d6ff;">"codemagic-mcp")

@server.style ="color: #d2a8ff;">tool()
style ="color: #ff7b72;">async style ="color: #ff7b72;">def style ="color: #d2a8ff;">analyze_code(code: style ="color: #ff7b72;">str, language: style ="color: #ff7b72;">str) -> style ="color: #ff7b72;">list[TextContent]:
    style ="color: style ="color: #6b7280;">#a5d6ff;">""style ="color: #a5d6ff;">"Analyze code style ="color: #ff7b72;">for issues and improvements."style ="color: #a5d6ff;">""
    analysis = style ="color: #ff7b72;">await style ="color: #d2a8ff;">run_analysis(code, language)
    style ="color: #ff7b72;">return [style ="color: #d2a8ff;">TextContent(type =style ="color: style ="color: #6b7280;">#a5d6ff;">"text", text =analysis)]

@server.style ="color: #d2a8ff;">tool()
style ="color: #ff7b72;">async style ="color: #ff7b72;">def style ="color: #d2a8ff;">generate_tests(code: style ="color: #ff7b72;">str) -> style ="color: #ff7b72;">list[TextContent]:
    style ="color: style ="color: #6b7280;">#a5d6ff;">""style ="color: #a5d6ff;">"Generate unit tests style ="color: #ff7b72;">for the given code."style ="color: #a5d6ff;">""
    tests = style ="color: #ff7b72;">await style ="color: #d2a8ff;">create_tests(code)
    style ="color: #ff7b72;">return [style ="color: #d2a8ff;">TextContent(type =style ="color: style ="color: #6b7280;">#a5d6ff;">"text", text =tests)]

MCP capabilities

Everything you need to build enterprise AI integrations.

MCP Server Development

Build custom MCP servers that expose your tools, data, and capabilities to AI models like Claude.

Tool Integrations

Create tool definitions that let AI models interact with your APIs, databases, and internal systems.

Context Management

Implement resource providers that give AI models access to relevant context from your data sources.

Prompt Templates

Build reusable prompt templates that ensure consistent, high-quality AI interactions.

Security & Auth

Implement secure authentication, authorization, and data access controls for MCP servers.

Multi-Server Orchestration

Connect multiple MCP servers for complex workflows spanning different tools and data sources.

MCP Use Cases

IDE Integrations

Build MCP servers that give AI coding assistants access to your codebase, documentation, and development tools.

Business Data Access

Let AI models query your CRM, ERP, and internal databases securely through MCP resource providers.

Custom Tool Suites

Expose domain-specific tools like code analysis, document processing, or API testing to AI assistants.

Workflow Automation

Create MCP tools that let AI models trigger and orchestrate business processes across your systems.

Development Process

01

Requirements Analysis

1 week

Understand your AI integration needs, data sources, and tool requirements.

02

Architecture Design

1-2 weeks

Design MCP server architecture, tool schemas, and resource providers.

03

Server Development

3-6 weeks

Build MCP servers with tools, resources, and prompts tailored to your needs.

04

Integration & Testing

2-3 weeks

Integrate with Claude/AI clients, thorough testing, and security validation.

05

Deployment & Support

Ongoing

Production deployment with monitoring, documentation, and ongoing support.

Frequently Asked Questions

MCP is a protocol that enables AI models to interact with external tools, data sources, and systems. It provides a standardized way to give AI assistants like Claude access to your custom capabilities.

MCP is currently supported by Claude (via the Claude desktop app and API), with growing adoption across the AI ecosystem. We can also help adapt MCP patterns for other platforms.

MCP servers run locally or on your infrastructure, giving you full control over data access. We implement authentication, authorization, and audit logging for enterprise-grade security.

Yes, we specialize in building MCP servers that connect to your existing APIs, databases, and tools. This lets AI models work with your data without data leaving your infrastructure.

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