Understanding MCP servers: generic vs. domain-specific approaches

Introduction: MCP Servers as APIs for LLMs

MCP (Model Context Protocol) servers are to Large Language Models (LLMs) what REST APIs are to applications: structured, standardized ways to interact with external data sources and tools. Like APIs, MCP servers vary significantly in design, from highly generic and flexible solutions to specialized, domain-specific ones.

In this post, we’ll delve deeper into these two approaches—generic versus domain-specific—and explain how thoughtful MCP server design can dramatically improve the usability and efficiency of LLM-powered applications.

Throughout this post, we'll reference the RAGmonsters dataset, a curated database containing detailed information about various fictional creatures, their characteristics, strengths, and weaknesses. This example will help illustrate practical scenarios clearly and make analogies intuitive when discussing different MCP server designs.

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REST APIs: A Useful Analogy

Consider traditional REST APIs:

• Generic REST APIs might have a single POST /query endpoint for raw SQL execution. Flexible, yes—but cumbersome for clients who must fully understand database internals.
• Domain-tailored REST APIs provide endpoints like GET /monsters/{id} or GET /monsters?type=dragon, making interactions intuitive and straightforward.

Similarly, MCP servers can choose their abstraction level depending on their use case, balancing ease-of-use against flexibility and implementation complexity.

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Generic MCP Servers: A Flexible Starting Point

A generic MCP server aims to be universally applicable, offering maximum flexibility to interact with different databases or tools without prior knowledge of their schemas or internal logic.

Example: PostgreSQL MCP Server with Single Query Tool

Consider the @modelcontextprotocol/server-postgres, an MCP server that provides a single endpoint, such as POST /query, accepting raw SQL queries and returning database results. This approach places minimal constraints on the type of queries the client (in this case, the LLM) can execute.

Pros

• ✅ Simplicity: Easy and fast to deploy without much setup.
• ✅ Universality: Compatible with virtually any PostgreSQL database.

Cons

• ❌ High Cognitive Load: The LLM must understand complex database schemas before it can effectively query.
• ❌ Inefficiency: Typically requires multiple preliminary queries to fully grasp the schema, resulting in increased latency and reduced efficiency.
• ❌ Security Concerns: Accepting raw SQL increases vulnerability to SQL injection if inputs are improperly handled.

If you'd like to see an example of a generic MCP server in action, you can check out the PostgreSQL MCP Server with LLM Chat Example on Clever Cloud, deploy it yourself, connect it to your preferred LLM, and experiment with it firsthand.

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Domain-Specific MCP Servers: A Tailored, Efficient Alternative

Domain-specific MCP servers offer specialized tools and endpoints adapted to the exact domain of the database or application they serve, greatly simplifying the LLM’s task.

Example: Custom PostgreSQL MCP Server for RAGmonsters

The RAGmonsters MCP server is built specifically to handle a database containing detailed information on various creatures, including their types, weaknesses, and strengths. Instead of a general query endpoint, this MCP server offers domain-focused tools like:

• getMonsterByName
• listMonstersByType

This approach abstracts the underlying database structure, allowing the LLM to make specific, high-level requests without needing to understand table schemas or write SQL.

Advantages

• ✅ Reduced Cognitive Load: The LLM interacts through intuitive, semantic tools.
• ✅ Performance Optimization: Each tool can be optimized for speed and efficiency.
• ✅ Enhanced Security: No direct SQL exposure to the LLM, reducing the risk of injection attacks.

Drawbacks

• ❌ Initial Development Overhead: More upfront planning and design are required.
• ❌ Reduced Flexibility: Significant schema changes require updates to the MCP server.

If you'd like to see an example of a domain-specific MCP server in action, you can explore the Custom PostgreSQL MCP Server for RAGmonsters. Follow the instructions to deploy it on Clever Cloud and test it yourself.

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When to Choose Generic vs. Domain-Specific

Choosing between generic and domain-specific MCP servers depends on several factors:

Factor	Generic MCP Server	Domain-Specific MCP Server
Development Speed	Quick initial setup	Requires initial planning and setup
Performance & Efficiency	Less efficient, more queries needed	Optimized, fewer queries needed
Security	More vulnerable due to raw SQL	More secure, no direct SQL exposure
Flexibility & Adaptability	Highly adaptable to schema changes	Requires modifications with schema changes
Usability for End Users	Complex, high cognitive load	Simple, intuitive tools

Key Questions to Guide Your Decision:

• Who are the primary users?

  • Developers exploring data or end-users seeking direct answers?

• What is the complexity of your database schema?

  • A complex schema benefits significantly from domain-specific abstraction.

• How critical are performance and security?

  • Domain-specific servers offer clear advantages here.

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Conclusion: Choosing the Right Abstraction Level

Understanding your project's specific needs will guide you toward the right choice, ensuring optimal interactions for your LLM-driven applications.

Want to explore further? Check out our examples, the generic PostgreSQL MCP Server with LLM Chat Example on Clever Cloud and the Custom PostgreSQL MCP Server for RAGmonsters on GitHub.