Model Context Protocol servers let AI agents reach beyond the codebase. They connect your agent to external APIs, databases, search engines, and services through a standardized protocol, so the agent can actually take action, not just write code.
1084 servers
An open source MCP (Model Context Protocol) server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments. - Quick Start - Prerequisites - Installation - Usage Examples - Configuration - Available Tools - Architecture - How It Works - MCP Client Integration - Performance Considerations - Troubleshooting -
A Model Context Protocol (MCP) server providing character-level index-based string manipulation. Perfect for test code generation where precise character positioning matters. LLMs generate text token-by-token and struggle with exact character counting. When generating test code with specific length requirements or validating string positions, you need precise index-based tools. This MCP server sol
MCP (Model Context Protocol) server for the Oyemi semantic lexicon. Provides deterministic word-to-code mapping and valence analysis for AI agents like Claude, ChatGPT, and Gemini. - Semantic Encoding: Convert words to deterministic semantic codes - Valence Analysis: Analyze text sentiment using lexicon-based valence - Semantic Similarity: Measure how similar two words are - Synonym/Antonym Lookup
A comprehensive Desktop Extension for searching Airbnb listings with advanced filtering capabilities and detailed property information retrieval. Built as a Model Context Protocol (MCP) server packaged in the Desktop Extension (DXT) format for easy installation and use with compatible AI applications. - Location-based search with support for cities, states, and regions - Google Maps Place ID integ