"Maintaining Consistent Behavior in System Prompts" matching MCP servers:

Automatically extracts actionable methodologies from articles and URLs, stores them in a vector database, and retrieves relevant methods to enhance user prompts for more effective AI interactions.

A simple MCP server for utilizing prompts defined in YAML files.

Provides real-time and scheduled bus information for Montevideo's public transport system.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.

Enables management and invocation of AWS Bedrock managed prompts with support for variable substitution, streaming responses, batch processing, and multiple AI models including Claude, Titan, Llama, and Mistral.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Local-first knowledge system for reasoning agents, exposing facts, evidence, documents, retrieval, and audit history through a thin stdio MCP server.

Enables access to Australian real estate data through the Realty In Au API, supporting property listings, agent/agency information, property details, school lookups, and property search with various filters.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables users to access the Realty In Ca1 API to search for residential and commercial property listings, view detailed property information, and retrieve neighborhood demographics or statistics. It supports filtering by geographic location, price range, building type, and other real estate characteristics.

Provides access to a universal design token system with 7 pre-built themes (colors, typography, spacing, motion) and multi-format export capabilities for Canva, Remotion, PPTX, CSS, and W3C JSON.

Cross-project memory for Claude Code, enabling local semantic recall and secure, git-versioned markdown storage of reusable knowledge across repositories.

A production-quality multi-agent research system with an arXiv MCP server and LangGraph-based research agents, providing search, details, and cached summaries via SQLite.

Enables real-time monitoring of system resources including CPU, GPU (NVIDIA, Apple Silicon, AMD/Intel), memory, disk, network, and processes across Windows, macOS, and Linux platforms through natural language queries.

A comprehensive MCP (Model Context Protocol) server for file system operations, providing Claude and other AI assistants with access to local files and directories.

Fetches, summarizes, and reviews GitHub code diffs with asynchronous processing for large diffs.