Easy Memory
Easy Memory MCP - Dual-engine embedding service with Qdrant vector store
Mcp Server Milvus Danchev
A Model Context Protocol (MCP) server for agentic retrieval and semantic search over unstructured and structured data using Milvus, a high-performance vector database. This server enables large language model (LLM) applications to efficiently index, store, and retrieve vector emb
Mcp Lancedb Node
Mcp Lancedb Node MCP server provides AI agents with powerful tools and integrations for automation workflows. Connect your AI assistant to Mcp Lancedb Node capabilities through the Model Context Protocol standard.
Forge Mcp Voxellinc
Forge is Voxell's hosted text-embedding API. This MCP server exposes two tools — embed (turn text into vectors) and list_models — so any MCP-compatible agent can generate embeddings for semantic search, RAG, clustering, and dedup.
Mcp Brain Server
Brain Server - MCP Knowledge Embedding Service is an MCP server on MCP.so — view details, tools, and install instructions.
Context Keeper
**Context Keeper** 基于LLM驱动的智能上下文记忆管理系统，专为AI Agent提供企业级记忆能力。
Gemfiremcpserverdemo
GemFireMCPServer is an MCP server on MCP.so — view details, tools, and install instructions.
Vector Search X402
x402 micropayment API for AI agents. In-memory vector store with cosine similarity search. For RAG pipelines. Pay per call with USDC on Base.
Kelnix Datamind Curator
AI-Ready Data & Context Engineering API. Connect any data source — PostgreSQL, CRMs, APIs — and get clean, structured, AI-ready data in seconds. Natural language queries, semantic vector search, automated PII redaction, deduplication, and AI-powered context building for RAG pipel
Memory Mcp 1file
A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents.
Mcp Server Ragdocs
An MCP server that provides tools for retrieving and processing documentation through vector search, both locally or hosted. Enabling AI assistants to augment their responses with relevant documentation context.
io.github.portel-dev/ncp
One MCP to Rule Them All. NCP consolidates over 50 scattered MCP tools into two unified tools (Find & Run). Your AI goes from confused to confident with 87% fewer tokens, zero tool confusion, and 5x faster responses. Perfect for teams drowning in MCP tool sprawl.
Voyageai Cli
MCP server for Voyage AI embeddings, reranking, and MongoDB Atlas Vector Search. Provides 11 tools for semantic search, document ingestion, cost estimation, and model exploration. Full RAG pipeline: chunk, embed, vector search, and rerank from any MCP client.
Ai Memory Mcp
Persistent memory for any AI assistant. Zero token cost until recall. Stores memories locally in SQLite, ranks by 6-factor scoring, returns results in TOON compact format (79% smaller than JSON). 17 MCP tools, 20 HTTP endpoints, 25 CLI commands. 4 tiers from keyword to autonomous