"Techniques for Scraping Dynamic Websites with JavaScript and Handling CAPTCHA or Proxy Issues" matching MCP servers:

Enables secure, runtime-authenticated MySQL database querying and mutation through dynamic tools, allowing AI assistants to list databases/tables, describe schemas, and perform CRUD operations.

Enables AI agents to dynamically register and query MySQL-compatible databases at runtime with built-in destructive SQL protection.

Context-efficient MCP server that executes OpenSearch DSL queries and returns synthesized output instead of raw JSON, reducing token usage by up to 90%.

Generates safe, scoped PostgreSQL DML tools for FastMCP agents, enabling controlled database interactions without raw SQL.

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

Enables secure, controlled access to existing relational databases via MCP, with API key authorization, read/write permissions, table-level allow/deny lists, SQL validation, rate limiting, audit logging, and a web management console. Supports PostgreSQL, MySQL, SQLite, SQL Server, and Oracle.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

A self-hosted MCP server that proxies MCP clients to Power BI, using your own Entra tenant and Azure subscription. It enables DAX queries, workspace listing, and dataset management while preserving user-specific row-level security.

A secure, read-only MySQL database proxy using MCP protocol, enabling SQL queries and table inspections via HTTP.

Generates FastMCP tools for PostgreSQL DML operations (insert, select, update, delete) per table based on schema introspection, with Pydantic models for input validation.

Enables natural-language querying of databases via SQLBot, with datasource discovery, metadata inspection, and report generation.

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.

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.

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 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.