CentralMind Gateway is a powerful tool designed to expose databases to AI Agents via MCP or OpenAPI 3.1, providing a secure bridge between your data and AI models. It automatically generates LLM-optimized APIs from your database schema and sample data, eliminating the need for direct SQL access and mitigating security risks. Supporting databases like PostgreSQL, MySQL, and Snowflake, it offers REST API and MCP server functionalities, including SSE mode.

This gateway seamlessly integrates with AI models and applications like LangChain and Claude Desktop, using function calls or Cursor via MCP. Key features include automatic API generation, PII protection, flexible configuration through YAML and plugins, and comprehensive monitoring with OpenTelemetry. Deployable as a binary or Docker container, CentralMind Gateway simplifies data access for AI, enhancing functionality while ensuring security and compliance. It supports various AI providers, including OpenAI, Anthropic, and Google Gemini, and offers features like row-level security and API key authentication.

Automated, LLM-Optimized API Generation

CentralMind Gateway automatically generates REST APIs or MCP servers from structured databases, leveraging LLMs to optimize them for AI agent interactions. It analyzes database schemas and sample data to create APIs tailored for LLM applications, eliminating the need for manual API design and coding. This automated process ensures that the generated APIs are not only functional but also semantically aligned with the requirements of AI models, facilitating more effective data retrieval and manipulation. For example, a data scientist can use the Gateway to expose a PostgreSQL database containing customer transaction data to an AI model for sentiment analysis, without writing any API code. The Gateway handles the complexities of data access and transformation, allowing the data scientist to focus on model development and analysis. This feature uses LLMs to understand the data and generate optimized API structures based on prompts.

Secure Data Access via MCP & REST

The Gateway provides secure data access through both MCP and REST APIs, mitigating security, compliance, and performance risks associated with direct SQL database access. It supports various authentication options, including API keys and OAuth, and implements PII protection through regex or Microsoft Presidio plugins. This ensures that sensitive data is masked or redacted before being exposed to AI models, maintaining data privacy and compliance with regulations like GDPR. For instance, a financial institution can use the Gateway to provide an AI-powered customer service chatbot with access to customer account information, while ensuring that sensitive data like social security numbers and account balances are protected. The Gateway's security features prevent unauthorized access and data breaches, safeguarding customer data and maintaining regulatory compliance. The implementation includes configurable authentication middleware and PII masking plugins.

Multi-Protocol & Database Support

CentralMind Gateway supports multiple protocols, including REST API and MCP Server with SSE mode, and a wide range of structured databases such as PostgreSQL, MySQL, ClickHouse, Snowflake, and more. This broad compatibility allows developers to integrate the Gateway into diverse environments and leverage existing database infrastructure. The multi-protocol support enables seamless integration with various AI models and applications, regardless of their preferred communication protocol. For example, a healthcare provider can use the Gateway to connect a legacy MySQL database containing patient records to a modern AI-powered diagnostic tool that communicates via MCP. The Gateway acts as a bridge between the old and the new, enabling the healthcare provider to leverage the power of AI without having to migrate their entire database infrastructure. The database support is implemented through database-specific connectors, and the protocol support is implemented through different server implementations.

Flexible Deployment & Configuration

The Gateway offers flexible deployment options, including standalone binaries, Docker containers, and Helm charts, making it easy to deploy and manage in various environments. It also provides a YAML-based configuration system and a plugin architecture for easy extension and customization. This flexibility allows developers to tailor the Gateway to their specific needs and integrate it seamlessly into their existing infrastructure. For example, a startup can deploy the Gateway on a Kubernetes cluster using Helm charts, while a larger enterprise can deploy it on-premises using standalone binaries. The YAML configuration allows developers to customize the Gateway's behavior, such as setting up API endpoints, configuring authentication, and enabling PII protection. The deployment flexibility is achieved through cross-platform compilation and containerization, and the configuration flexibility is achieved through a modular design and a plugin system.