"Developing an API using NestJS, Prisma, and PostgreSQL" matching MCP servers:

Manage Prisma Postgres databases with ease

Enables AI agents to manage Prisma Postgres databases and database workflows, including creating databases, running migrations, executing SQL queries, and managing backups, through natural language.

A production-oriented MCP server for PostgreSQL that exposes database operations like query execution, schema introspection, and table metadata to MCP clients such as Claude Desktop and VS Code.

A secure MCP server that lets AI assistants directly interact with PostgreSQL databases via tools like create_table, list_tables, and execute_sql, plus a web configurator for managing connections.

Read-only MCP server for PostgreSQL, enabling schema discovery, table metadata, and safe SELECT queries via READ ONLY transactions.

A production-ready MCP server that connects AI assistants to any PostgreSQL database with 25 tools and role-based access control.

A general-purpose PostgreSQL MCP server with full read-write SQL access, atomic multi-statement transactions, and schema inspection. Works with any PostgreSQL instance — local, Supabase, AWS RDS, or self-hosted — and connects to Claude, Cursor, Windsurf, or any MCP-compatible AI client.

Provides AI-driven PostgreSQL database management with secure OAuth 2.1 authentication, enabling users to administer, monitor, and query databases with support for extensions like pgvector, PostGIS, and pg_cron.

MCP server for managing notes with CRUD tools. It uses the same notes service as the GraphQL API, enabling natural language interaction with notes.

A robust server-side application that implements Model Context Protocol (MCP) for file operations, providing authentication and modular REST APIs for managing files, users, and posts.

A Model Context Protocol server that provides read-only access to PostgreSQL databases. This server enables LLMs to inspect database schemas and execute read-only queries.

Full-featured MCP server that exposes 36 tools for interacting with PostgreSQL databases, covering schema introspection, query execution, data exploration, performance monitoring, security auditing, and maintenance.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

Enables comprehensive PostgreSQL database monitoring, analysis, and management through natural language queries. Provides performance insights, bloat analysis, vacuum monitoring, and intelligent maintenance recommendations across PostgreSQL versions 12-17.

A Model Context Protocol server that enables powerful PostgreSQL database management capabilities including analysis, schema management, data migration, and monitoring through natural language interactions.

Facilitates management and optimization of PostgreSQL databases, offering analysis, setup guidance, and debugging, while ensuring secure and efficient database operations.

Enables natural language interaction with PostgreSQL databases through Amazon Q for querying data, listing tables, and describing schemas. It provides secure, read-only access with automatic row limits to ensure efficient database exploration.

Enables MCP clients to safely query one or more PostgreSQL databases with read-only tools and explicitly approved write operations.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

A Python MCP server that enables schema discovery, read-only SQL queries, table previews, and index/relationship analysis on PostgreSQL databases.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables AI assistants like Claude to interact with MongoDB databases through standardized MCP tools. Supports full CRUD operations, aggregations, and natural language queries with Clean Architecture and dual transport modes (STDIO/HTTP).

Enables AI assistants to safely interact with PostgreSQL databases, perform queries, inspect schemas, and analyze query performance.