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

Manage Prisma Postgres databases with ease

A demonstration implementation of Model Context Protocol (MCP) using NestJS framework, allowing developers to build MCP-compatible applications with playground testing capabilities.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

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 NestJS module for building Model Context Protocol (MCP) servers using decorators to expose services as tools, resources, and prompts. It features auto-discovery, a built-in playground UI, and support for multiple transports including SSE and Stdio.

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

A production-ready NestJS backend template with built-in MCP server enabling AI agents to query your data via standardized protocol, featuring RAG pipeline, semantic search, and comprehensive developer tooling.

Build MCP servers inside NestJS applications using ordinary controllers with decorators for tools, resources, and prompts, supporting authentication and authorization.

Give your AI coding agents the superpower to observe your NestJS application's runtime state in real-time.

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.

Enables agents and IDEs to generate and verify NestJS microservices with hexagonal architecture, JSON:API contracts, and mandatory security headers. Supports declarative spec-based module generation, refactoring existing services, quality checks, and per-repository inventory and auditing.

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 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 LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.