The Pros and Cons of Building an In-House MCP Server: Balancing Secure Information Management and AI Utilization

As the use of generative AI and knowledge bases expands, more companies are considering building their own “MCP servers” (Managed Content Provider servers). An MCP server securely manages documents and data used as a knowledge base and provides them for search and AI responses. However, building one requires significant resources and careful decision-making.

This article explains in detail the advantages and disadvantages of building an in-house MCP server and introduces key points for successful implementation.

Who This Article Is For

This article is particularly helpful for:

• IT leaders considering enhancing internal information management
• System administrators in security-sensitive industries (e.g., healthcare, finance, public institutions)
• Planners and developers aiming to establish a high-quality knowledge base for AI utilization
• Information management and legal departments seeking stronger data governance
• Educational and welfare sector personnel aiming to combine AI use with accessibility considerations

This information is ideal for those seeking to protect information assets while boosting overall organizational productivity.

Benefits of Building an In-House MCP Server

1. Enhanced Security and Privacy

By hosting an MCP server internally, the risk of exposing confidential or personal data to external environments is significantly reduced. Encryption, access control, and compliance measures can be customized based on internal policies.

Example
Healthcare institutions are increasingly managing patient data with in-house MCPs to avoid the risks of external cloud services.

2. High Degree of Customization

You can design search algorithms, access management, and metadata structures optimized for your workflows and knowledge structures. It’s possible to customize document classification for specific departments and support proprietary RAG (Retrieval-Augmented Generation) configurations.

Example
In manufacturing, design documents and manuals are finely tagged per product, with search features customized for development teams.

3. Continuous Knowledge Asset Development and Quality Improvement

An MCP server promotes the accumulation and organization of information, allowing for the gradual building of a valuable organizational knowledge asset. Incorporating regular updates and reviews helps maintain the freshness and reliability of information over time.

Example
Financial institutions promptly reflect regulatory changes in manuals, ensuring that AI responses provided to employees are always based on the latest information.

4. Improved Compatibility with AI Agents

Establishing a high-quality knowledge base significantly enhances the performance of generative AI and AI agents, reducing the risk of hallucinations and making practical, business-level AI assistance more achievable.

Drawbacks of Building an In-House MCP Server

1. High Initial Costs and Ongoing Maintenance Burden

Building a server, infrastructure setup, security measures, and securing development and operations teams require considerable cost and human resources. Post-deployment maintenance and troubleshooting also impose continuous operational burdens.

Example
Some small businesses attempted to build their own MCPs but had to migrate to cloud services due to skyrocketing operational costs.

2. Need for Technical Knowledge and Specialized Skills

Advanced skills are needed for indexing design, search optimization, vulnerability management, and more. Without sufficient in-house expertise, construction and operations may fail.

Example
Poorly optimized database structures led to significantly degraded search accuracy and user dissatisfaction in some cases.

3. Limited Flexibility for Scaling

If user numbers or data volumes rapidly grow, on-premises servers may struggle to scale flexibly, potentially necessitating future rearchitecting or hybrid cloud adoption.

4. Risk of Security Incidents

Unlike external cloud providers, you must manage security updates and threat countermeasures yourself, increasing the risk of information leaks due to management errors.

Key Points for Successful Implementation

• Thorough Preliminary Research and Requirement Definition
  Clearly define data scale, user numbers, and security requirements.

• Start Small with a Minimum Viable Product (MVP)
  Build a small initial system to identify problems before scaling.

• Collaborate with Specialized Partners
  Partner with experts in security, infrastructure, and search system design.

• Establish Continuous Review and Improvement Cycles
  Regularly monitor usage and maintain a system for updates and optimization.

Conclusion: Building an MCP Server Requires Clear Purpose and Resource Commitment

Building an in-house MCP server can greatly enhance information autonomy and security, but it also comes with challenges such as high costs, operational burdens, and technical requirements.

Key Takeaways:

• Building an MCP in-house provides high flexibility and security
• However, initial investment and continuous operational costs must be carefully evaluated
• A phased, small-start approach increases chances of success
• Designing with accessibility in mind ensures usability for all

When considering implementation, clarify “why we need an in-house MCP” and “how much we can manage internally.” A clear strategy and strong organizational setup are the keys to successful deployment.