"AI Prompting Techniques and Reasoning Methods" matching MCP servers:

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.

Adds a deep_reasoning tool that consults stronger reasoning models (e.g., DeepSeek R1) to produce full reasoning traces for complex problems, helping the agent shape and cross-check its answers.

An MCP server that provides a multidimensional philosophical framework for prompt engineering by mapping intent across ten distinct branches of thought. It generates a principled construction basis, including active constructs and spectrum tensions, to guide the creation of structured and intentional prompts.

Provides reasoning budget estimates for AI tasks, making effort and time trade-offs visible through a compact control interface.

Enables multi-step AI reasoning by sending prompts to OpenRouter, performing a verification pass, and returning both responses with provider reasoning fields when available.

A self-hosted MCP server that provides tools for structured reasoning, confidence calibration, and detecting recurring gaps in AI outputs, aiming to reduce workload by improving verification and attention allocation.

MCP server for deep algorithmic and mathematical reasoning, wrapping any OpenAI-compatible LLM endpoint to return only the final distilled answer without reasoning traces. Supports per-call model and endpoint overrides, defaulting to vibethinker-3b via LM Studio.

Describe your AI use case in plain English, get ranked model recommendations with cost estimates and tradeoff reasoning. Covers 62 models across 29 providers. Available as a web app (BYOK + guest tier) and as an MCP server for Claude Desktop and Cursor — same recommendation engine, two interfaces.

An advanced MCP server that gives AI assistants persistent memory with machine-learning-powered semantic understanding, enabling branching memory, semantic search, and project analysis.

Cybersecurity AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Connect AI agents to Jev AI (jev-ai.pro) for classification, scoring, yes/no checks, advisory action assessment, batched typed decisions and saved judges. Returns structured answers and probabilities using your Jev AI API key.

Model Context Protocol server for Verlon AI that exposes gates, logs, recommendations, and experiments as MCP tools, enabling coding agents to inspect and manage AI infrastructure natively.

Transforms HTML into Figma designs using only the user’s design system, ensuring correct component usage or safe fallback to primitives, while continuously learning from each build to improve mapping accuracy and consistency.

Audits AI-bot visibility: robots.txt per-bot for 22 AI user-agents (GPTBot/ClaudeBot/PerplexityBot/etc), Cloudflare flags, JSON-LD, sitemap, llms.txt, SPA shell, plus cross-model brand mentions via Perplexity + OpenRouter. 0-100 score. SSRF-guarded, spend-capped.

Proofof AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Unified MCP server for managing local model runtimes (Ollama, LM Studio, etc.), enabling provider-agnostic discovery, lifecycle management, hardware-fit checks, and delegated inference.

Enables AI photo generation, editing, and video creation from MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

MCP server for MarkItUp's AI image-annotation pipeline. Generate polished marketing-visual variations of any screenshot, regenerate, AI outpaint, and remove backgrounds — powered by Claude analysis + Gemini rendering.

Enables a host AI agent to trigger a multi-agent debate, running N-rounds where agents critique each other's answers, then synthesizes a consensus recommendation with ranked options.