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Why this server?
Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings.
Why this server?
Enables seamless AI integration via Ollama's Deepseek model, providing protocol compliance and automatic configuration.
Why this server?
A bridge that enables seamless integration of Ollama's local LLM capabilities into MCP-powered applications, allowing users to manage and run AI models locally with full API coverage.
Why this server?
An open protocol server that implements Anthropic's Model Context Protocol to enable seamless integration between LLM applications and RAG data sources using Sionic AI's Storm Platform.
Why this server?
A Model Context Protocol server that enables LLMs to interact with Elasticsearch clusters, allowing them to manage indices and execute search queries using natural language.
Why this server?
A Model Context Protocol server built as a Model Context Protocol (MCP) server that provides advanced web search, content extraction, web crawling, and scraping capabilities using the Firecrawl API.
Why this server?
Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.
Why this server?
An implementation of the Model Context Protocol server that enables using Google's Gemini AI models (specifically Gemini 1.5 Pro) through Claude or other MCP clients via the Model Context Protocol.
Why this server?
A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.