"Sailfish OS" matching MCP servers:

Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.

Enables AI assistants to interact with Meilisearch through a standardized interface, supporting index and document management, search capabilities, settings configuration, task monitoring, and experimental vector search.

Wraps n8n with an MCP server and vector storage to enable semantic search, management, and execution of automated workflows. It integrates with other tools to make workflows searchable and orchestratable within a larger automation ecosystem.

A cloud-based vector memory service that provides AI assistants with persistent storage, semantic search, and entity management via the Model Context Protocol. It features multi-tenant isolation and bidirectional synchronization with macOS and Google contacts and calendars.

A TypeScript implementation of the Model Context Protocol server that enables creation, management, and semantic search of memory streams with Mem0 integration.

MCP server for a self-hosted RAG system that enables AI tools to search and retrieve grounded answers from locally ingested documents via MCP tools, with local embeddings and no API key required.

Local-first semantic memory server with project indexing for AI assistants. It enables AI assistants to store, retrieve, and search memories and project code using embeddings and vector search.

A persistent semantic memory layer for AI coding agents, enabling storage and retrieval of text with vector embeddings via MCP tools.

A local-first, zero-LLM memory system and MCP server that gives AI assistants a searchable, structured persistent memory using a spatial metaphor.

A Model Context Protocol server that provides intelligent file reading and semantic search capabilities across multiple document formats with security-first access controls.

Allows LLMs to access, scan, and search photos on connected iOS devices via USB using libimobiledevice and ChromaDB. It supports semantic search, metadata filtering, and automated file organization for efficient media management.

Enables querying MaxKB knowledge bases through MCP, supporting vector, hybrid, and full-text retrieval of relevant segments, as well as listing knowledge bases, documents, and workspaces.

A Model Context Protocol server for generating text embeddings using OpenAI, Anthropic, or Ollama, with tools for single and batch embedding operations.

Enables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.