Databases MCP Repositories

Perform CRUD operations on Postgres databases with a focus on automation and safety. Features include a read-only mode and query plan checks using the `EXPLAIN` statement before execution.

Streamline data operations by providing tools for querying, updating, and maintaining database systems efficiently.

Integrates semantic and graph-based document retrieval using a hybrid system of Neo4j and Qdrant, enabling enhanced search capabilities. Supports semantic search via document embeddings and graph context expansion based on relationships.

Execute SQL queries on a ClickHouse cluster, list all databases, and retrieve tables within a specified database.

Enables inspection of MySQL database schemas and execution of read-only queries. Provides safe query execution within READ ONLY transactions and supports Docker.

Enables secure interaction with Microsoft SQL Server databases, allowing users to list tables, read data, and execute SQL queries through a controlled interface. Provides structured access for database exploration and analysis.

Provides access to the AACT database for analyzing clinical trial data and generating reports on therapeutic landscapes. Facilitates querying and understanding of clinical trial data structures through a series of tools that enable direct interaction with the database.

Perform seamless CRUD operations on a PostgreSQL database with type safety, allowing efficient management of user data and post entities. Utilize a robust MCP-compatible tool interface for reliable database interactions.

Connects AI assistants to StarRocks databases for executing SQL queries and exploring database schemas with ease. Provides capabilities for data visualization and detailed data overview retrieval without complex setups.

Store and retrieve information from AI interactions using a Neo4j backend, facilitating advanced graph querying and memory management. Enhances performance and scalability for complex knowledge graph applications.

Connects AI models to a PostgreSQL database, executing SQL queries and retrieving schema information through a standardized protocol. Enables real-time data access and handles connection errors gracefully.

Connects to SQL Server databases for efficient access data analysis, enabling execution of SQL queries and dynamic exploration of database schemas. Facilitates identification of sensitive data and management of user permissions within the environment.

Expose TigerGraph graph database operations as structured tools and URI-based resources for MCP agents, facilitating schema introspection, query execution, and vertex/edge upsert through a Python interface.

Converts natural language into SQL statements using a two-step generation process to minimize inaccuracies and ensure reliability for non-technical users.

Connect and execute queries on a MySQL database using the MCP protocol for efficient interaction. Provides a standardized API for seamless database operations.

Interact with local systems, databases, and external services through file operations, database management, and GitHub integration. Perform secure and efficient commands and transactions to enhance AI applications with real-world capabilities.

Interacts with the Xano API to manage database operations, providing tools for secure authentication, workspace management, and table content operations. Supports type-safe API interactions using TypeScript and offers improved error handling with detailed messages.

Connect to MySQL databases to perform natural language queries, retrieve table and column metadata, and execute SQL SELECT queries through a simple MCP interface. Designed for LLM clients to access live MySQL data seamlessly.

Provides a persistent, searchable working memory for AI-assisted development, enabling automated recall of context from previous sessions while managing insights effectively. Integrates with ChromaDB to enhance workflow continuity across complex tasks.

Facilitates interaction with PostgreSQL databases by enabling read-only execution of SQL queries and inspection of database schemas. Provides structured data access while maintaining data integrity through read-only transactions.

Enables semantic similarity search and vector collection management using ChromaDB in a Dockerized environment. Supports customized document collections and search queries through a Python script.

Python-based MCP server that facilitates communication with various data sources such as databases and web services through a JDBCX server interface.

Fireproof ledger database with multi-user sync

Process and manage Outlook emails with capabilities for storage, search, and analysis. Features include date range filtering, semantic search through vector embeddings, and support for summarization and automatic categorization.

Manage and interact with various databases including PostgreSQL, MySQL, and Firestore. Execute queries, list tables, and export data seamlessly to enhance database management tasks.

Enables querying of Azure Cosmos DB data using natural language through a conversational interface. Facilitates secure and efficient interactions between AI models and the database by translating user queries into database requests.

Analyzes PostgreSQL database configurations, assesses performance metrics, and provides security evaluations along with optimization recommendations.

A complete property management system that facilitates the management of properties, bookings, financial reporting, and owner-tenant communication through a FastAPI backend and a React frontend.

Interact with PostgreSQL databases by performing safe read and write operations with enhanced schema metadata and transaction management. Leverage the advanced capabilities of PostgreSQL while maintaining strict safety controls.

Simple Snowflake MCP server that works behind a corporate proxy. Read and write (optional) operations