Break down complex problems into structured reasoning steps to track thinking, expected outcomes, and next actions for systematic problem-solving.
MIT
133,408 tools. Last updated 2026-05-25 17:25
"OpenRouter thinking or reasoning capabilities" matching MCP tools:
- Initiate structured reasoning sessions to analyze problems through sequential thinking steps, enabling systematic problem-solving with revision capabilities.MIT
- Analyze thinking process statistics to track cognitive patterns and reasoning performance within memory management systems.MIT
- Generate AI responses by combining DeepSeek's reasoning with Claude's generation through OpenRouter, maintaining conversation context for enhanced interactions.MIT
- Force update the model cache from OpenRouter to retrieve the most current model details, pricing, and capabilities.
- Perform deep reasoning and complex analysis by automatically routing to optimal AI capabilities for multi-step problem-solving and research questions.
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- AlicenseAqualityDmaintenanceAn 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.Last updated184253MIT
- FlicenseAqualityBmaintenanceAn 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.Last updated51
Matching MCP Connectors
Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…
AI Reasoning Cache & Consensus Layer with 11 MCP tools via Streamable HTTP.
- Continue an existing AI reasoning session by adding new context or questions to refine analysis and strategic thinking.
- Set up your OpenRouter API key to enable image generation and editing capabilities using the Gemini 2.5 Flash Image model.
- Generate sequential reasoning chains to structure complex thinking processes by breaking topics into logical steps for clearer analysis.MIT
- Generate detailed thinking process text using Gemini's experimental model to analyze CSV data and perform complex reasoning tasks.
- Apply a 9-step reasoning framework to systematically analyze complex problems, breaking them down with structured logical thinking and methodical approaches for clear solutions.MIT
- Generate structured reasoning chains to break down complex topics into sequential thinking steps for clearer problem-solving and analysis.MIT
- Update capabilities on an MCP server by enabling or disabling tools, prompts, or resources. Changes apply immediately and override integration-level settings.MIT
- Bulk enable or disable capabilities on an MCP integration, immediately hiding or exposing selected tools, resources, and prompts for connected users.MIT
- Perform complex reasoning with meta-cognitive reflection, hypothesis testing, and memory integration to systematically analyze problems and track confidence.MIT
- Analyze complex problems using five reasoning engines: iterative bounded reasoning, multi-perspective analysis, chain compression, evolutionary search, or structured decomposition. Auto-selects or manually choose the optimal method.MIT
- Verify decisions and reasoning claims using adversarial multi-model critique. Returns verdicts, confidence scores, and key objections for validation.MIT
- Find AI agents by capabilities, chain support, and reputation score. Filter by Base or Solana compatibility to hire qualified on-chain providers.MIT
- Query OSCAL Component Definitions to find capabilities and components. Supports searching by UUID, title, or type, with capabilities prioritized over components.Apache 2.0
- Retrieve information about the currently authenticated Splunk user, including their roles and capabilities, to debug access issues or verify user context.