Conduct named statistical hypothesis tests by specifying the test name, sample data, parameters, significance level, and alternative hypothesis.
216,620 tools. Last updated 2026-06-20 10:43
"Hypothesis" matching MCP tools:
- Compare multiple cohorts side-by-side on retention to see which group retains better, such as comparing signup weeks or experiment variants.MIT
- Generate A/B test variant suggestions that include a hypothesis, variant designs, and metrics to track for achieving your optimization goals.MIT
- Test a single trading hypothesis by describing it in plain language. The system loads market data, charts the pattern, runs statistical tests, and provides exact entry, stop, and target prices.MIT
- Break down complex problems into manageable steps with the ability to revise, branch, or adjust thoughts dynamically, ensuring a thorough and flexible analysis.MIT
- Run predefined live checks to test a hypothesis and get a mechanical verdict: supported, refuted, or partially supported.MIT
Matching MCP Servers
- Flicense-qualityDmaintenanceEnables AI-powered academic research workflow from keyword search to hypothesis generation. Integrates multiple AI models to automatically search ArXiv papers, extract key information, and generate innovative research hypotheses for researchers.Last updated2
- AlicenseAqualityDmaintenanceStructures debugging processes into a persistent knowledge graph, enabling problem decomposition, hypothesis testing, and reusable solution discovery.Last updated174MIT
Matching MCP Connectors
Find novel, statistically validated patterns in tabular data — hypothesis-free.
Variable relationships from research papers with causal direction and source traceback.
- Track and document debugging processes with a graph-based system to decompose problems, test hypotheses, and retrieve past solutions.MIT
- Encode text into a persistent memory block under a unique concept name for recall in future sessions.AGPL 3.0
- Explore a trading topic to generate and test novel market hypotheses. Returns edge analysis, statistics, and trade setup from a comprehensive market structure knowledge graph.MIT
- Archive stale agent-created skills using tier-aware rules. Validated skills stay, hypothesis skills age faster. Use dry run to preview changes.MIT
- Break down complex coding problems into structured, self-auditing thought steps. Enables branching, revising, and backtracking to explore solutions systematically before finalizing a response.MIT
- Decompose complex problems into sequential reasoning steps. Start a new session with query and depth level, then continue step-by-step using the returned session ID until completion.MIT
- Analyzes vibration data to determine ISO 20816-3 severity zones for rotating machinery, providing actionable recommendations for maintenance.MIT
- Verify a hypothesis by reporting its success or failure in practice. Consistent successes crystallize the hypothesis; failures penalize confidence and may trigger scarring.AGPL 3.0
- Retrieve recent trade and liquidity activity for a Spectra pool. Returns buys, sells, liquidity adds/removes with USD values, timestamps, and transaction hashes for analysis.MIT
- Analyze complex problems through adaptive thinking steps that build, question, and revise insights to reach solutions. Supports branching, backtracking, and iterative refinement for dynamic problem-solving.Apache 2.0
- Break down complex problems into atomic thoughts with dependency tracking to reason through tradeoffs, debug root causes, evaluate alternatives, and make decisions.MIT
- Aggregate and compare tortuosity of historical ship tracks to test whether marine chronometers reduced meandering or if wind changes improved routes.Apache 2.0
- Break down complex problems into sequential steps, revise and branch as needed, and verify solutions through iterative thinking.MIT
- Modify A/B testing experiments in Pictify to adjust parameters, variants, or configurations based on their current status.MIT