jOOQ▌

by martinellich
Quickly access jOOQ documentation with AI — search guides, examples, and API references instantly.
Access jOOQ documentation through AI
best for
- / Java developers using jOOQ for database access
- / Learning jOOQ SQL query building techniques
- / Setting up jOOQ code generation
- / Database-specific jOOQ implementation
capabilities
- / Search jOOQ documentation for specific topics
- / Get SQL query building examples
- / Retrieve code generation documentation
- / Get database-specific support information
- / Access Query DSL reference documentation
- / Get advanced jOOQ feature documentation
what it does
An MCP server that provides AI models with access to jOOQ documentation, including SQL examples, code generation guides, and database-specific information.
about
jOOQ is a community-built MCP server published by martinellich that provides AI assistants with tools and capabilities via the Model Context Protocol. Quickly access jOOQ documentation with AI — search guides, examples, and API references instantly. It is categorized under developer tools.
how to install
You can install jOOQ in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
license
Apache-2.0
jOOQ is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
jOOQ MCP Server
A Model Context Protocol (MCP) server that provides AI models with access to jOOQ documentation. This Spring Boot application uses Spring AI to expose jOOQ documentation as MCP tools, allowing AI systems to query and retrieve information about jOOQ features, SQL examples, and best practices.
Features
The MCP server provides the following tools:
- searchDocumentation: Search jOOQ documentation for specific topics
- getSqlExamples: Get SQL query building examples for specific operations
- getCodeGenerationGuide: Retrieve jOOQ code generation documentation
- getDatabaseSupport: Get database-specific support information
- getQueryDslReference: Get Query DSL reference for specific statement types
- getAdvancedFeatures: Access documentation for advanced jOOQ features
Getting Started
Prerequisites
- Java 21 or higher
- Maven 3.6+
Running the Application
-
Clone the repository:
git clone <repository-url> cd jooq-mcp -
Build the project:
./mvnw clean install -
Run the application:
./mvnw spring-boot:run
The MCP server will start and be available for connections from MCP clients.
Docker Deployment
-
Build the JAR file:
./mvnw clean package -
Build the Docker image:
docker build -t jooq-mcp . -
Run the Docker container:
docker run -p 8080:8080 jooq-mcp
Fly.io Deployment
This application is configured for deployment on Fly.io:
-
Install Fly CLI and authenticate:
brew install flyctl # or your preferred installation method fly auth login -
Deploy the application:
./mvnw clean package fly deploy
The application includes health checks at /actuator/health and is configured with auto-scaling.
Using with MCP Clients
This server can be used with any MCP-compatible AI client. The server exposes tools that allow AI models to:
- Search jOOQ documentation by keyword
- Retrieve specific SQL examples and code snippets
- Access database-specific configuration information
- Get guidance on code generation setup
- Find information about advanced jOOQ features
Configuration
The application can be configured via application.properties:
# MCP Server Configuration
spring.ai.mcp.server.name=jooq-documentation-mcp
spring.ai.mcp.server.version=1.0.0
spring.ai.mcp.server.type=SYNC
spring.ai.mcp.server.capabilities.tool=true
# Cache Configuration
spring.cache.type=caffeine
spring.cache.caffeine.spec=maximumSize=100,expireAfterWrite=1h
# jOOQ Documentation Crawler Configuration
jooq.documentation.crawler.max-depth=4
jooq.documentation.crawler.max-urls-per-section=100
jooq.documentation.crawler.timeout-ms=10000
jooq.documentation.crawler.cache-duration-hours=24
# Server Configuration - SSE Buffer Settings
server.tomcat.max-http-response-header-size=64KB
server.tomcat.max-swallow-size=10MB
Example Usage
When connected to an MCP client, you can ask questions like:
- "How do I create a SELECT statement in jOOQ?"
- "Show me examples of jOOQ INSERT operations"
- "What databases does jOOQ support?"
- "How do I configure jOOQ code generation?"
- "How do I use transactions in jOOQ?"
The server will fetch the relevant documentation and provide detailed answers with code examples.
Architecture
The application consists of:
- JooqDocumentationService: Main service class with @Tool annotated methods for MCP integration
- LocalJooqDocumentationService: Provides local documentation indexing and full-text search with TF-IDF scoring
- InvertedIndex: Implements advanced full-text search capabilities with relevance scoring
- JooqDocumentationCrawler: Crawls and fetches jOOQ documentation for local storage
- JooqDocumentationFetcher: Handles parsing and extraction of documentation content
- McpConfiguration: Spring configuration for MCP tool registration
- Caching: Caffeine-based caching to improve performance
Key Features
- Local Documentation Storage: Documentation is stored locally in
src/main/resources/docs/for faster access - Full-Text Search: Advanced search using TF-IDF scoring for better relevance
- Efficient Indexing: In-memory inverted index for fast document retrieval
- Code Example Extraction: Automatic extraction and categorization of code examples
Testing
Run the test suite:
./mvnw test
Development
The application uses:
- Spring Boot 3.5.4
- Spring AI 1.0.0 with MCP Server support
- JSoup for HTML parsing
- Caffeine for caching
To add new tools, create methods annotated with @Tool in the JooqDocumentationService class.
FAQ
- What is the jOOQ MCP server?
- jOOQ is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for jOOQ?
- This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
jOOQ is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated jOOQ against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: jOOQ is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
jOOQ reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend jOOQ for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: jOOQ surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
jOOQ has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, jOOQ benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired jOOQ into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
jOOQ is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.