"A service for finding LinkedIn user profiles by name and location" matching MCP servers:

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Enables AI agents to generate fake user profiles and companies using the Random Profiles API with automatic API key handling.

An MCP server that reads and edits OrcaSlicer profiles, expanding the full inheritance chain and tracking the provenance of every value.

Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Oracle Service Cloud (beta): https://www.cdata.com/download/download.aspx?sku=KOZK-V&type=beta

A throwaway HTTP MCP server that empirically tests whether Cursor invokes tools by exact name or munges them, to inform case normalization decisions.

Provides an interactive checklist tool that allows AI agents to present step-by-step instructions to users through an automatically opened terminal UI. It enables agents to guide users through manual tasks and wait for completion, skipping, or feedback before proceeding.

Exposes user, membership, and role administration tools via MCP, acting as a thin passthrough to a coordinator API with RBAC enforced by the coordinator using caller bearer tokens.

Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.

A minimal Model Context Protocol (MCP) service for integration with external platforms. Provides CRUD operations, reference data fetching, and authentication capabilities.

A Model Context Protocol (MCP) service for integration with external platforms, providing CRUD operations for 23 entity types through a standardized MCP interface.

It enables AI agents to parse user agent strings into structured data such as browser, OS, device type, engine, and bot status, with pay-per-call micropayments via x402 and no API key or signup required.

MCP server that enables Claude to pause and ask clarifying questions via Emacs.

A production-ready generic FastMCP server template with SQLAlchemy async CRUD, enabling rapid bootstrapping of MCP data-management services. It provides registry-driven CRUD, FK resolution, conflict versioning, and multiple transports.

A reusable MCP HTTP server with OAuth 2.1 that turns any JSON-RPC handler into a production-ready endpoint with dynamic client registration, PKCE, refresh tokens, and OpenAPI docs.

A unified HTTP/HTTPS service that exposes Model Context Protocol (MCP) functionality over HTTP endpoints, allowing clients to list available tools and call them through a standardized API.

Provides GPU-accelerated gradient boosting model training and inference through a cloud service. Enables AI agents to train models on NVIDIA A10G GPUs and get fast cached predictions with portable model artifacts.

Independent MCP service module for Poco, providing analytics and management tools such as daily usage analysis and service introspection.

Enables Codex to clarify requirements via native MCP elicitation controls, supporting single/multiple-choice and free-text questions with recommended answers and a discuss-first option.