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MCP Servers

Connect AI Agents to Real Systems

Deploy MCP servers that allow AI agents and LLM applications to securely interact with databases, APIs, observability platforms, and production infrastructure.

Available MCP Servers

Deploy ready-to-use MCP integrations directly from the NexNodo Marketplace.

MCP Catalog:

MCP Server PostgreSQL

Enable AI agents to query live relational data, execute structured database operations, and interact with production business data in real time.

MCP Server Grafana

Allow AI systems to access live infrastructure metrics, operational dashboards, and production monitoring environments for automated analysis and decision making.

MCP Server Elasticsearch

Give AI applications access to logs, indexed operational data, and large-scale search infrastructure for intelligent monitoring and automated troubleshooting.

MCP Server MongoDB

Allow AI agents to interact with document databases, retrieve operational data, and execute dynamic workflows using flexible schema-based data structures.

MCP Server MySQL

Enable AI agents to query and operate on production MySQL databases, executing structured reads and writes against live business data.

MCP Server MariaDB

Give AI applications direct access to MariaDB relational data for reporting, automation, and real-time operational queries.

MCP Server Redis

Allow AI agents to read and write cached data, session state, and real-time queues backed by Redis infrastructure.

MCP Server OpenSearch

Give AI systems access to indexed search data and analytics for intelligent monitoring and automated troubleshooting at scale.

MCP Server Prometheus

Allow AI systems to query live metrics and alerting data for automated infrastructure analysis and anomaly detection.

MCP Server Kafka

Enable AI agents to consume and produce event streams, connecting AI workflows to real-time data pipelines and messaging infrastructure.

MCP Server RabbitMQ

Allow AI agents to publish and consume messages, integrating AI workflows with existing asynchronous messaging infrastructure.

MCP Server MinIO

Give AI applications access to object storage for retrieving, indexing, and managing files as part of automated workflows.

MCP Server Qdrant

Enable AI agents to perform vector search and retrieval against production embeddings for RAG and semantic search use cases.

MCP Server Weaviate

Allow AI systems to query AI-native vector data for semantic search, retrieval, and knowledge base applications.

MCP Server Loki

Give AI agents access to aggregated log data for automated troubleshooting, root-cause analysis, and operational intelligence.

MCP Server Trino

Enable AI agents to run federated SQL queries across distributed data sources for large-scale analytics and reporting.

MCP Server Keycloak

Allow AI systems to interact with identity and access data for automated user management and security operations.

MCP Server Superset

Give AI agents access to dashboards and data exploration tools for automated reporting and business intelligence workflows.

MCP Server ClearML

Enable AI agents to query experiment tracking and MLOps data for automated model monitoring and training pipeline management.

MCP Server Memgraph

Allow AI agents to query graph data and relationships in real time for connected-data analysis and reasoning.

Build With MCP Servers

AI Database Assistants

Allow AI agents to retrieve and query real production data directly from databases.

Autonomous Infrastructure Monitoring

Enable AI systems to analyze infrastructure metrics and detect operational anomalies automatically.

Private Enterprise AI Agents

Connect internal AI assistants to business systems, databases, and operational infrastructure.

AI-Powered DevOps Automation

Allow AI agents to access observability tools and automate infrastructure workflows.

Real-Time Operational Intelligence

Enable LLM systems to analyze live operational data and generate actionable insights.

Connected AI Environments

Build AI systems capable of interacting with real-world production environments securely.

The Future of AI Agents Connected to Real Infrastructure

AI Application

(Open WebUI, Dify, Flowise)

MCP Server Layer

(Secure AI access to external systems)

Connected Systems

Databases · APIs · Monitoring Platforms · Infrastructure Services · Internal Business Tools

AI Can Execute Real Actions

Query Live Data · Analyze Infrastructure · Trigger Automations · Execute Workflows · Generate Decisions

Without MCP, AI can answer questions. With MCP, AI can interact with your infrastructure.

Build Autonomous AI Systems on Infrastructure You Control

Combine GPU infrastructure, Kubernetes environments, open-source AI applications, and MCP servers to build AI systems capable of interacting with real databases, observability platforms, APIs, and production infrastructure.