"Access GEO Biomedical Datasets" matching MCP servers:

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Integrates RAGFlow's knowledge base API with Claude Desktop for document retrieval, semantic search across multiple datasets, and intelligent query refinement using DSPy.

Enables querying and retrieving content from Confluence through CQL searches and page content fetching, allowing Claude to seamlessly access information stored in Confluence workspaces.

Enables interaction with the RAGFlow API to manage knowledge base datasets and conduct AI-driven chat sessions. Users can list datasets, create chat assistants, and retrieve or query information from specialized knowledge bases.

Enables building, querying, and publishing structured knowledge to the decentralized Geo knowledge graph using GRC-20, with tools for graph operations, DAO governance, and file ingestion.

Enables listing datasets, creating chat assistants, and chatting with them via RAGFlow API.

Equips AI coding agents with 62 production-grade tools across 28 modules for persistent memory, live GitHub scouting, UI/UX design, DevOps, security, performance auditing, and SEO/AEO/GEO optimization, enabling automated, development workflows.

A structure-aware MCP server for querying the SPOKE biomedical knowledge graph, enabling entity resolution, schema introspection, path finding, and safe Cypher queries for biomedical knowledge inference.

Provides a comprehensive Model Context Protocol interface for RAGFlow, enabling AI models to perform semantic retrieval, manage datasets, and handle document chunks. It supports advanced features like GraphRAG and RAPTOR for sophisticated knowledge base management and natural language querying.

Enables AI agents to query self-hosted knowledge bases through hybrid retrieval and list available datasets, providing grounded, retrieval-augmented answers.

Provides persistent, graph-based memory for AI agents using Neo4j and vector embeddings, enabling semantic recall across sessions via MCP.

Free service management tools — playbooks, benchmarks, and instant service health analysis. DigitalCore MCP gives you free access to service management expertise directly in your AI assistant. Run a Service Reality Check to score your service health in 60 seconds. Access strategy playbooks for ser

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Enables querying Wikidata via SPARQL, with convenience tools for instances, subclasses, properties, and geo-spatial queries.

MCP server enabling LLMs to query a local Calibre Content Server for ebook metadata, chapters, and content in HTML or Markdown.

This MCP server provides governed read access to the Analytos Brain knowledge graph, enabling content and GTM agents to retrieve approved entities and relationships with access control and citations.

Wikivibe MCP is a public read-only Model Context Protocol server for Wikivibe, a Russian/English knowledge base about AI coding, vibe coding, AI agents, MCP, developer tools, SEO/GEO, Telegram bots, integrations, databases and deployment workflows. It also exposes the public VibeDesign catalog of ready-made templates, layouts, components, dashboards, animations and source links.

Integrates with Get Notes API to search and retrieve knowledge from configured knowledge bases with AI-powered synthesis and raw recall capabilities.

Intelligent knowledge base management tool that enables searching, browsing, and analyzing documents across multiple datasets with smart document analysis capabilities.