"OpenRouter thinking or reasoning capabilities" matching MCP servers:

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

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

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.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

An MCP server that brings difficulty-adaptive, multi-path reasoning to Claude Code. It implements the Actor-Critic-Planner-Reflexion (ACPR) pipeline for deep research synthesis.

A powerful MCP server that enhances LLMs with advanced sequential thinking capabilities, supporting 19 thinking modes for structured reasoning and complex cognitive tasks.

MCP server providing a model-agnostic subagent tool backed by OpenRouter, supporting multi-model Fusion and orchestration patterns.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.

Provides an MCP server that decomposes complex problems into ordered, isolated reasoning contexts, yielding compressed summaries before discarding intermediate steps. Enables sequential or parallel step execution with optional verification for more reliable LLM reasoning.

An MCP server for discovering and querying over 300 AI models available on OpenRouter. It enables users to list, search, filter, compare, and get detailed information about models with pricing, context limits, and capabilities.

Enables AI assistants to consult other AI models via OpenRouter for help with coding tasks.

Gives AI assistants image generation and editing capabilities through OpenRouter, supporting multiple models, style presets, variations, and batch operations.

A Python MCP server that lets MCP hosts call OpenRouter models for chat, image generation, embeddings, and model search via FastMCP with .env support and retry handling.

Provides access to 400+ AI models from OpenRouter, enabling users to chat with models like GPT-4, Claude, Gemini, and Llama, compare responses across multiple models, and retrieve model information with pricing details.

An MCP server that provides access to 400+ AI models via OpenRouter, enabling chat, comparison, and document analysis through Claude.

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

Strategic BDI cognitive reasoning engine for AI agents. Goal decomposition DAGs, multi-factor utility scoring, risk evaluation, and adaptive replanning over MCP.

A 66-tool reasoning pipeline that intercepts prompts to classify intent, check past mistakes, and generate execution plans, enabling any LLM to think harder and avoid repeating errors.