"IP address geolocation lookup service" matching MCP servers:

Enables semantic search across documents and code repositories using RAG (Retrieval-Augmented Generation) with vector embeddings. Automatically indexes PDF documents and performs relevance-scored lookups through ChromaDB and sentence transformers.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.

Enables character management and semantic search for the Auto-Movie application through WebSocket communication. Supports creating characters with personality/appearance descriptions and finding similar characters using natural language queries with embedding-based similarity matching.

This MCP server provides semantic document search and retrieval, enabling AI assistants to search documents, search categories, and retrieve category hierarchies using the Model Context Protocol.

A clean architecture backend API that registers and semantically searches data using vector embeddings, acting as an MCP context provider to connect AI models to external data.

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.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

Enables Claude Desktop to search private documents using Azure AI Search and perform web searches with Bing, providing AI-enhanced results with source citations through Azure AI Agent Service or direct Azure AI Search integration.

MCP bridge to a multimodal RAG service, enabling hybrid search and Q&A over documents with tools for knowledge base queries and health checks.

Exposes infocepo.com infrastructure (LLM, ChromaDB, S3, Docker registry, service discovery) as MCP tools for AI agents.

A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.

A Model Context Protocol server that enables users to perform third-party enrichment lookups for security observables (IP addresses, domains, URLs, emails) through services like VirusTotal, Shodan, and others.

A minimal RAG service that exposes a vector index for document retrieval via REST and MCP, allowing querying for relevant document chunks and returning a suggested LLM prompt.

Enables AI-assisted chiller troubleshooting by exposing MCP tools to retrieve operational data, alarms, telemetry, and service history from MongoDB Atlas, plus vector and hybrid search over knowledge bases.

Enables AI coding assistants to automatically scan, store, and query API endpoints from codebases, providing instant lookup and semantic search to reduce context switching and token consumption.

A pluggable, observable modular RAG service framework that exposes tool interfaces via the MCP protocol, enabling AI assistants like Copilot and Claude to directly invoke knowledge retrieval and reasoning capabilities.

An independent memory service for AI agents that stores and retrieves facts with keyword and semantic search, context management, and a plugin-based architecture.

Personal memory service using semantic vector retrieval and knowledge graphs to persist long-term context, supporting memory evolution and conflict labeling for the same entity.

Enables AI agents to search through OpenShift service notification logs using semantic search powered by ChromaDB and sentence transformers, helping find relevant notifications based on problem descriptions with metadata enrichment and variable interpolation support.