Retrieve the current thinking profile from the system configuration, falling back to a default structure if the file is missing.
AGPL 3.0
281,412 tools. Last updated 2026-07-10 07:47
"Tools for slow thinking, step-back reasoning, and contextual memory capabilities" matching MCP tools:
- Document AI reasoning and decision-making for audit trails. Log analysis, plans, and observations without altering code.MIT
- Analyze complex problems through sequential thinking, track assumptions, and manage multi-step reasoning with confidence scoring and session-based context.MIT
- Access the complete Astria operating guide to learn available tools, recommended workflows, and best practices for persistent memory management.MIT
- Apply step-by-step reasoning with web grounding to complex questions. Ideal for math, logic, comparisons, and multi-step arguments. Returns reasoned answers with numbered citations. Supports recency, domain, and search context filters.MIT
- Replace a previous thought with updated reasoning, preserving the original in revision history. Corrects incomplete or wrong thinking.MIT
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- Record numbered thinking steps for structured reasoning, enabling complex problems to be broken into sequential steps with branching and revision. Manage session history, reset when needed, and finalize to persist outcomes to Memory Bank.MIT
- Record each step of a reasoning process by adding numbered thoughts to a persistent chain. Ideal for analysis, debugging, design, and research tasks that require structured, sequential thinking.MIT
- Access documentation and usage guides for n8n workflow automation tools to understand available capabilities and implementation methods.MIT
- Reads and returns the current thinking profile from the system configuration, automatically falling back to default values if the file is missing.AGPL 3.0
- Break down complex problems into structured reasoning steps to track thinking, expected outcomes, and next actions for systematic problem-solving.MIT
- Compute cycle times of completed task groups segmented by project template to identify slow workflows and bottleneck steps. Optionally include per-step durations for deeper analysis.MIT
- Get step-by-step Arthas command recipes for diagnosing common production symptoms like high CPU, memory leaks, and slow requests. Omit arguments to list available topics.MIT
- Explore available resources, tools, and capabilities within the Axom MCP Server to support AI agents with environment discovery and tool chaining.MIT
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- Execute complex browser tasks autonomously using AI reasoning for multi-step web interactions, detailed research, and handling dynamic websites.MIT
- Solve complex math, science, and coding problems with transparent, step-by-step reasoning using advanced AI. Ideal for tasks requiring detailed explanations and logical processes.MIT
- Analyzes complex problems through adaptive thinking steps, recommends appropriate tools for each stage, and tracks progress toward solutions.MIT
- Initiate structured reasoning sessions to analyze problems through sequential thinking steps, enabling systematic problem-solving with revision capabilities.MIT
- Identifies slow ClickHouse queries and diagnoses root causes such as full scans, memory issues, and aggregation inefficiencies.MIT