Check Ollama server status and available models to see if free local inference is available for processing large contexts.
MIT
260,964 tools. Last updated 2026-07-05 10:01
"Understanding Inference Models" matching MCP tools:
- List models available for inference via Tuning Engines API. Includes platform models and your deployed trained models.MIT
- Send chat messages to run text inference using multiple LLMs. Choose from 11 models priced between $0.003-$0.10 USDC per request.MIT
- Perform high-speed chat completions using Groq's inference with open models such as Llama 3, Mixtral, and Gemma.AGPL 3.0
- Search and use Hugging Face models, datasets, and spaces through inference, information retrieval, and authentication operations.Mozilla Public 2.0
- Browse curated AI models organized by category. View featured and popular models across sections like 'Recently Added', 'Image Generation', and 'Video'.MIT
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Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.
- Retrieve daily LLM usage, cost trend, and model breakdown for a specific agent to optimize inference spending.MIT
- Retrieve LLM inference usage per agent with token consumption, GPU cost, and request counts. Pinpoint which agents and teams consume the most resources and cost.MIT
- Retrieve a comprehensive list of supported AI models from the AiChat API, organized by provider including GPT-4/5, DeepSeek, Grok, and GLM models.MIT
- Find AI models for generation, editing, and analysis. Search by keyword, category, or owner, and filter by sort options to discover models before running them.MIT
- Retrieve all available JEPA inference schedules for analyzing attack paths in your infrastructure graph.Apache 2.0
- List local Ollama models and retrieve queryable paid route labels for accessing AI models with payment options.MIT
- Download prediction challenge inference data for specified periods to a local .parquet file, with optional polling for availability.MIT
- List available AI models and pricing. Filter by category or provider to compare costs and discover models.MIT
- Retrieve the status and results of a specific inference run using its run ID.Apache 2.0
- Retrieve a list of models from the SAS Model Repository. Specify a maximum number of models to return.Apache 2.0
- Run data tests on models, sources, snapshots, and seeds, and execute unit tests on SQL models to ensure data quality and accuracy in your dbt projects.Apache 2.0
- Retrieve detailed information about specific inference data periods for CrowdCent prediction challenges, enabling analysis of datasets and submission requirements.MIT
- Check which open-source models are currently served by the ParalleliX network to select the appropriate model for parallel inference tasks.MIT
- Retrieve an agent's inference budget, showing monthly limit, current spend, and whether overages are rejected or warned.MIT