MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.
A server that enables seamless integration between local Ollama LLM instances and MCP-compatible applications, providing advanced task decomposition, evaluation, and workflow management capabilities.
An MCP server that lets AI agents delegate domain-specific tasks to local Ollama models, using purpose-built specialists for structured tasks like config generation, parsing, and validation.
A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.
Routes AI tasks to appropriate local LLM models (quick, coder, MoE, thinking) with automatic model selection, multi-backend support (Ollama, llama.cpp, Gemini), and parallel processing capabilities.
Intelligent LLM orchestrator that automatically routes tasks to the most appropriate AI model (Gemini, Qwen, Ollama, LM Studio) based on task characteristics, enabling distributed processing and parallel execution across local and network services.
Enables multi-round brainstorming debates between multiple AI models like GPT, DeepSeek, and Ollama to produce synthesized final outputs. Users can orchestrate parallel model interactions where AI agents critique and refine each other's ideas to reach a consolidated conclusion.
An MCP server that queries multiple Ollama models and combines their responses, providing diverse AI perspectives on a single question for more comprehensive answers.
A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.
A Model Context Protocol server that provides standardized interfaces for interacting with Ollama API, offering JSON responses, error handling, and intelligent guidance for LLM-based API calls.
An AI router that connects applications to multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek, Ollama, etc.) with smart model orchestration capabilities, enabling dynamic switching between models for different reasoning tasks.
A Model Context Protocol (MCP) server that connects GraphDB's SPARQL endpoints and Ollama models to Claude, enabling Claude to query and manipulate ontology data while leveraging various AI models.
Discovers LLM models in real time from cloud providers and local Ollama instances, returning compatibility profiles and live pricing so AI agents can route tasks to the cheapest viable model without breaking tool calls or context clipping.
A meta-MCP server that uses Llama AI as an orchestrator to intelligently route requests and coordinate workflows across multiple MCP services like Stripe, GitHub, and databases. Enables complex multi-service operations with AI-driven decision making and parallel execution capabilities.
Privacy-first local MCP hub for coordinating multiple AI providers from Claude Code, supporting local Ollama seats and cloud providers with safety routing.
A high-performance control plane for Ollama-based local LLM sessions with background memory consolidation, hybrid cloud planning, and real-time fleet monitoring.
Bridges Llama models with Claude Desktop through Ollama, enabling privacy-first local AI operations with 10+ built-in tools for file operations, web search, calculations, and custom model deployment. Features streaming support, hybrid intelligence workflows, and extensive Python ecosystem integration for research, development, and enterprise applications.
Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.