"Exploring MCP Server Model Context Protocols for Research Paper Creation" matching MCP servers:

A Model Context Protocol (MCP) server that enables MCP clients like Claude Desktop to interact with protocols.io, a popular platform for sharing scientific protocols and methods.

MCP server for exploring and querying Supabase databases with interactive React widgets for schema browsing, table viewing, and SQL execution.

A production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.

A basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.

Enables AI-powered Ghost CMS blog management through Claude Desktop with content generation, image creation, and complete post management. Integrates Google Gemini for content generation and Flux/Imagen for feature images with GitHub OAuth authentication.

A simple learning-focused MCP server that demonstrates basic functionality with tools for mathematical operations, system information, and email validation, plus sample file resources. Perfect for understanding MCP protocol basics and testing integrations.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

An MCP server that connects to the Paper WebSocket API for managing canvas node operations. It enables users to list, create, update, and delete nodes and documents on the Paper platform.

Enables fixed-owner authoring and auditing of Bethesda game content, covering Creation Kit tools, TES records, Papyrus scripts, assets and archives, BMKB knowledge, authenticated Vortex operations, runtime verification, packaging, and release readiness. All target-changing operations require explicit confirmation, context snapshots, archive receipts, and authorization notes, while read-only knowledge and audit targets remain available for earlier Bethesda titles and Fallout 76.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

An MCP server for downloading academic papers from multiple sources using intelligent routing and year-aware priority selection. It enables users to retrieve metadata and download single or batch PDFs by DOI or URL.

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

MCP server for technical research in the TOTVS Protheus ecosystem, enabling AI agents to query official documentation, community knowledge bases, and release notes through structured tools. It supports runtime error debugging and ADVPL code generation.

Provides up-to-date AI model names and pricing from models.dev, solving model hallucination by fetching recently released models.

Enables AI assistants to interact with Square's Connect API through the Model Context Protocol standard, allowing for operations like managing customers, processing payments, and handling inventory.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

Provides structured web search capabilities optimized for technical and software development content via providers like OpenRouter. It enables AI agents to perform research and retrieve relevant technical data in a consistent, programmatic JSON format.

A minimal local MCP server that wraps any Claude Messages API-compatible upstream into a unified ask_model tool. It enables MCP clients to interact with these models through a standard tool interface using stdio transport.

An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.

Configurable MCP server that lets you define LLM-powered tools via JSON, enabling easy integration of multiple models (GPT, Gemini, Claude, etc.) as MCP tools without writing Python code.