"Obfuscated string with gethostbyname and bxss.me domain" matching MCP servers:

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

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

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

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 and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.

Enables LLMs to discover and invoke CRUD tools and read-only resources for generated services, allowing direct interaction with the same data exposed by the REST API.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Enables users to interact with PostgreSQL databases through natural language, with GitHub OAuth authentication and role-based access control.

Enables role-based order management through MCP tools, allowing users to view and refund orders according to their permissions (USER, MANAGER, ADMIN) with audit logging and JWT authentication handled by a FastAPI client.

Enables AI assistants to perform CRUD operations on a SQLite database, with all tools protected by Google OAuth 2.0 authentication.

It enables AI assistants to discover and invoke CRUD operations as MCP tools and read application data through MCP resources, allowing natural-language interaction with the generated backend.

It enables LLMs to interact with generated REST APIs by exposing CRUD operations as MCP tools and readable records as MCP resources. This lets AI clients discover and manage API data through the Model Context Protocol.

A FastAPI-based MCP server orchestrated with Docker Compose, integrating Redis caching and TimescaleDB for time-series data management.

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

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 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.