Context over copy-paste: our Model Context Protocol (MCP) development experience

Model Context Protocol (MCP) connects large language models (Claude, Gemini, others) directly into development environments through platforms like Cursor. Rather than working with isolated snippets, it provides AI with direct access to repositories, infrastructure, and project context.

What this enables

• Repository awareness: AI analyses actual codebases, not generic examples.
• Infrastructure understanding: Recognition of specific stacks, dependencies, and constraints.
• Contextual recommendations: Suggestions that align with existing system architecture.
• Reduced iteration cycles: Potential for faster issue resolution.

Our experience with implementation

One of our engineers integrated GitHub's MCP into his workflow. The difference was immediate: instead of describing problems to AI, the assistant could examine the codebase directly. Recommendations became specific to our project structure and coding patterns.

Why context matters

When AI works with the same information developers have, suggestions become actionable rather than theoretical.

Current adoption

Early adopters are reporting more efficient problem solving and faster feature development with MCP integration.

The shift appears to be from treating AI as an external consultation tool to integrating it as part of the development environment itself.

Security considerations

Before connecting your development environment to any AI service, consider:

• Data exposure: AI gains access to your complete codebase
• Intellectual property: Proprietary algorithms and business logic become visible
• Access controls: Ensure sensitive repositories aren't inadvertently exposed
• Compliance requirements: Evaluate legal obligations around sharing code with external services

The productivity benefits are significant, but proper security measures are essential.

Evaluating MCP for your team

If you're considering AI integration in your development process, we can share our implementation experience and help evaluate whether MCP fits your specific workflow and security requirements.

Contact us to discuss how contextual AI development might work for your team.