Get AI-recommended mental models for problem-solving by describing your challenge in natural language.
Apache 2.0
133,950 tools. Last updated 2026-05-25 01:39
"Reliable sources for use in training language models" matching MCP tools:
- Import pre-loaded training data from Intigriti, PortSwigger, and other sources to enhance security testing skills for bug bounty hunting.MIT
- Search your Talonic workspace for documents, fields, sources, or schemas matching a natural-language query. Returns ranked results across all entity types in one call.MIT
- Retrieve available voice synthesis models with IDs and descriptions for text-to-speech operations in the All Voice Lab MCP Server.MIT
- Enable, disable, or register custom models for an integration, affecting availability across all workspaces. Returns number of models updated.MIT
- Create new content entries in Contentrain CMS with automatic system field generation, supporting localized models and draft/publish status management.
Matching MCP Servers
- Alicense-qualityCmaintenanceProvides comprehensive access to Strava API for marathon training and race analysis, enabling language models to query athlete data, analyze training patterns, track performance metrics, monitor heart rate zones, and detect injury risks.Last updated1MIT
- Flicense-qualityDmaintenanceLaunches multiple Browser-Use agents to automatically test websites for UI bugs, broken links, accessibility issues, and other technical problems on both live and localhost sites.Last updated794
Matching MCP Connectors
Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.
An interactive portfolio built for AI conversations. Browse work, services, and book calls.
- Retrieve localized metadata for Teamfight Tactics augments, including names, descriptions, tiers, and image URLs, exported in CSV format. Specify a language code to access data in your preferred language.MIT
- Train a brand-consistent LoRA from 20-50 sample images. Returns a lora_id for use with ComfyUI and SDXL-family models. Requires a user-owned training endpoint.
- Create box plots from SQL query results on CSV or Parquet data sources to visualize statistical distributions and identify outliers in your data.MIT
- Retrieve a list of AI models available through Alephant for your credential scope. Enables you to see which models you can access.ISC
- Create bar charts from SQL query results on CSV, Parquet, or database sources to visualize data relationships and trends for analysis.MIT
- Download specific training datasets from CrowdCent prediction challenges to a specified .parquet file path for model training and analysis.MIT
- Retrieve coding style guidelines in Markdown format for a specified programming language to ensure consistent code quality and maintainability.MIT
- Create strip plots from SQL queries on CSV or Parquet data sources to visualize relationships between variables with optional color coding for additional dimensions.MIT
- Create histogram visualizations from SQL query results on CSV, Parquet, or database sources. Generate distribution plots for data analysis and business intelligence.MIT
- Retrieve available training datasets for CrowdCent prediction challenges to prepare data for model development and analysis.MIT
- Retrieve names and descriptions of all dbt models in your environment for comprehensive analysis and management.
- Retrieve and filter machine learning models from your ZenML workspace with sorting and pagination options.MIT
- Visualize SQL query results as line charts from CSV, Parquet, or database sources to analyze trends and patterns in data.MIT