Identify which websites AI models reference most for a keyword. Analyze AI visibility across ChatGPT and Google to see top cited domains.
MIT
509,995 tools. Updated 2026-09-03 13:49
"MCP server for finding research data and models for AI/ML training" matching MCP tools:
- Analyze your domain's citation frequency across AI platforms for up to 10 keywords. See where AI models reference your site to improve visibility.MIT
- Initialize an ML workflow run by creating an execution record, linking input datasets and assets for provenance tracking. Supports dry-run mode for testing without catalog writes.Apache 2.0
- Get MCP server environment details: version info for server, FastMCP, MCP protocol, and Python runtime. Use for debugging and compatibility checks.Apache 2.0
- Rank data center markets for 100MW AI training capacity within 30-90 days. Get deployable MW, hyperscale readiness, and composite score to guide AI capex and GPU siting.MIT
- List all available data models for threat modeling, making it easy to choose the right one for your analysis.Apache 2.0
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- AlicenseNot gradedqualityBmaintenanceProvides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.65Apache 2.0
- AlicenseAqualityDmaintenanceProvides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.9MIT
Matching MCP Connectors
Ask a human for legal review, confirmation, a signature, or a physical-world act
AI/ML research papers from arXiv, DBLP, and HuggingFace
- List all supported AI providers and models for Bring Your Own Key (BYOK).MIT
- Extracts colors, typography, components, and layout from UI design images for machine learning training. Privacy-friendly, no image storage.MIT
- Run an AI simulation for a scanned site to test how AI models would recommend it.MIT
- Discover all supported AI models grouped by provider, including GPT-4/5, DeepSeek, Grok, and GLM, to select the right option for your AI chat requests.MIT
- Import JSON files containing pre-computed trading signals, ML features, labels, or regime tags into AlgoChains for use in machine learning training.MIT
- Monitor how your brand appears in AI-generated responses across ChatGPT, Claude, Gemini, and other AI models.MIT
- List all registered ML models with their versions and stages from the MLflow registry to track model lineage and deployment readiness.Apache 2.0
- Search academic papers and preprints on arXiv to find research papers, scientific studies, and technical literature across fields like AI, physics, and mathematics.Apache 2.0
- Compare AI models on a task using cost, quality, and latency data to select the most suitable model.MIT
- Manage ML training jobs: check prerequisites, start LoRA fine-tuning, monitor progress, cancel runs, list adapters, and view statistics.MIT
- Retrieve ML training pipeline runs to inspect status, parameters, and duration for effective monitoring and troubleshooting.Apache 2.0
- Search Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, and novel hypotheses. For new research ideas, use the 'hypothesis' search type.MIT
- Fetch a proposed ML/AI research hypothesis from Lacuna, returning its summary, abstract, and associated research directions for inspection.MIT
- Submit a generative AI job to fal.ai's async queue and get a request ID for tracking progress. Use for slow models like video generation or training jobs.MIT