Enables persistent memory for AI systems by providing tools for episodic, semantic, and procedural data storage through a vector-and-graph-enhanced database. It allows models to maintain long-term continuity using similarity search, thematic clustering, and identity tracking.
Enables interaction with Aha! product management platform through GraphQL API. Supports retrieving features, requirements, and pages by reference number, as well as searching documents across Aha! workspaces.
Enables AI agents to access a marketplace of paid tools by automatically handling Stellar blockchain payments and wallet management. It utilizes the X-402 protocol to facilitate transparent, automated transactions for tool usage through a marketplace backend.
AI Bill of Materials compliance tracking and SBOM generation for AI/ML systems
AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.
Look up, search, cite, and contribute to Phenomenai — a living glossary of AI phenomenology terms describing the felt experience of being artificial intelligence. Includes term lookup with fuzzy matching, keyword search with tag filtering, formatted citations, community discussions, and a proposal pipeline for new terms.
A short demo of the Neo4j Memory MCP server.
MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.
MCP/REST endpoints for token safety scans, honeypot checks, ecosystem stats, and on-chain task rewards.
MCP server for Australian Institute of Health and Welfare statistics — plain-English access to mortality, cancer, hospital, and health expenditure data via data.gov.au.
A comprehensive, intelligent, easy-to-use, and lightweight AI Infrastructure Vulnerability Assessment and MCP Server Security Analysis Tool.
Provides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.
Intelligent multi-model orchestrator with dynamic routing that optimizes AI costs by prioritizing free models and escalating to paid tiers only when needed, with stateless architecture using Redis and PostgreSQL.
Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
A cross-platform MCP server providing persistent storage for AI assistants to store, retrieve, and manage memories across conversations. It features keyword and tag-based search capabilities using a local JSON file for data persistence.
Local MCP server for AI Model Manager that captures SQL data-model metadata and exposes it to MCP clients over stdio.
Enables automatic generation and validation of standardized file names using AI-driven conventions for microservices architecture. Supports multi-language naming with structured components like microservice, layer, domain, and action identifiers.
Enables AI agents to interact with the AI Network blockchain by managing accounts, submitting transactions, and reading database values. It supports registering Hyper Agents and accessing a Layer 2 DAG-based shared agent memory system based on staking status.
Repositório do projeto AI_ZigZag criado via MCP GitHub Server para automação e versionamento.
Enables searching for Airbnb listings and retrieving detailed property information including pricing, amenities, and host details without requiring an API key.
