"ollama" matching MCP servers:

Delegates tasks from an Anthropic-backed Claude Code session to Ollama-backed Claude Code sessions, allowing them to run side-by-side without sharing environment variables.

MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.

Enables Google Antigravity CLI to offload token-heavy workloads to local Ollama models through MCP tools for code drafting, summarization, chunked map-reduce, and JSON extraction, reducing cloud token usage.

Enables Claude Code to delegate sub-tasks to a local Ollama model through a single tool that accepts a prompt, optional system prompt, and model name and returns the full generated response. This routes bulk or mechanical work to a free local model so Claude's own tokens are reserved for tasks that need Claude-level reasoning.

A server that enables seamless integration between local Ollama LLM instances and MCP-compatible applications, providing advanced task decomposition, evaluation, and workflow management capabilities.

Hosts local MCP servers on Windows, enabling connection of local AI models (like Gemma) to external tools without cloud dependency.

Provides three MCP servers for Claude Code to access free/low-cost LLM models: GLM (Zhipu), Kimi (Moonshot), and local Ollama, enabling chat, vision, and offline tasks via natural language.

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.

Evaluates task suitability for local models before cloud API calls, routing to Ollama or similar to reduce costs.

A local stdio MCP server for running single-turn prompts across multiple model providers (OpenAI, Ollama, OpenRouter), allowing agents to fan out the same prompt to several models and combine the output.

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.

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.

AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

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.

Enables Claude Code to offload small coding tasks to local Ollama machines and free or paid AI providers, choosing the cheapest available option while enforcing quotas, budgets, and Claude's final review.

Real-time cluster health monitoring, pre-request NLMS latency prediction, and intelligent prompt routing across multi-instance LLM backends (vLLM, Ollama, SGLang, TGI).

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.

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.

Enables MCP clients to interact with a local AI agent through Ollama, providing tools for checking weather, current time, and available models, while tracing calls to Langfuse.