"OpenRouter thinking or reasoning capabilities" matching MCP servers:

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.

Enables LLMs and agents to verify multi-hop relational claims before asserting them, using zero-token relation-algebra proofs with precision guarantees. It supports opt-in calibration guards for entity normalization and relation transitivity.

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.

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.

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.

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.

Provides AI agents with deterministic symbolic math capabilities through 21 tools for algebra, calculus, transforms, and DSP, preventing hallucinations by delegating computations to a SymPy engine.

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.

Simple sequential thinking MCP in python

Provides a comprehensive creative thinking tool with methods like structured process, perspective shift, and constraint-based innovation to enhance divergent thinking.

Lets a Codex parent delegate bounded work to explicitly approved OpenRouter model/provider routes with strict permission controls, selected-file review, and approval-gated artifact creation.

Enables coding agents to obtain probabilistic decisions from Jev AI via OpenRouter for classification, scoring, and validation, with tools like jev_check, jev_classify, jev_score, and jev_evaluate.

Turns Claude Code into a recursive analysis engine that builds explorable decision trees from IF/THEN chains, enabling thorough problem exploration and structured synthesis of action plans.

MCP server that helps AI assistants automatically find, filter, and rank the best AI models for a specific task using the OpenRouter API.

Exposes OpenRouter's image generation, video generation, image-to-video, and model discovery to local AI clients such as Claude Code, OpenCode, OMP, and Codex over stdio. It lets clients list available models, generate images and videos, track and download video jobs, and resume in-flight jobs without blocking past client tool timeouts.

A Model Context Protocol server that provides unified access to 400+ AI models from 30+ providers through OpenRouter's API, enabling seamless integration with Claude Code.

Provides seamless access to 200+ AI models through OpenRouter's unified API, featuring multi-model collaboration, vision support, intelligent benchmarking, and collective intelligence capabilities for enhanced decision-making.

Facilitates structured creative thinking through sequential thought processing, helping users shift from reactive problem-solving to proactive outcome creation using structural tension analysis and stage-based thinking workflows.