MCPs tagged with # Observability

Beelzebub is an advanced honeypot framework that utilizes AI and large language models (LLMs) to realistically simulate system interactions, enabling the detection and analysis of sophisticated cyber attacks. The platform supports modular service definitions via YAML, integrates with observability stacks, and supports multiple protocols including MCP, which is used to detect prompt injection against LLM agents. Designed for security researchers and professionals, it enables the creation of distributed honeypot networks for collaborative global threat intelligence.

• ⭐ 1,680
• MCP
• mariocandela/beelzebub

PMCP implements a Model Context Protocol (MCP) server in Go, enabling natural language access and manipulation of Prometheus metrics. It maintains full consistency with the Prometheus HTTP API and supports a robust, type-safe interface for seamless integration with MCP-compatible clients. The server offers complete Prometheus API coverage and supports multiple transport methods, including HTTP and Server-Sent Events. Its modular architecture is designed for performance, extensibility, and effective error handling.

• ⭐ 3
• MCP
• yshngg/pmcp

VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

• ⭐ 87
• MCP
• VictoriaMetrics-Community/mcp-victoriametrics

Pydantic Logfire MCP Server provides an MCP-compatible interface to access, analyze, and query telemetry data sent to Pydantic Logfire. It allows LLMs to retrieve distributed traces, perform SQL queries on telemetry databases, and generate links for trace inspection. The server can be integrated with well-known MCP clients and supports configuration for secure access with read tokens.

• ⭐ 124
• MCP
• pydantic/logfire-mcp

Metoro MCP Server is an implementation of the Model Context Protocol (MCP) that enables seamless integration between Kubernetes observability data and large language models. It connects Metoro’s eBPF-based telemetry APIs to LLM applications such as the Claude Desktop App, allowing AI systems to query and analyze Kubernetes clusters. This solution supports both authenticated and demo modes for accessing real-time cluster insights.

• ⭐ 45
• MCP
• metoro-io/metoro-mcp-server

Last9 MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide seamless integration between AI agents and production observability data. It allows tools and agents to fetch live logs, metrics, traces, events, and alerts from Last9 systems, supporting a range of development environments and IDEs. This enables faster debugging, automated code fixes, and insightful context directly within local development workflows.

• ⭐ 46
• MCP
• last9/last9-mcp-server

Grafana MCP Server implements the Model Context Protocol (MCP) to interface with Grafana and its ecosystem. It enables querying, modifying, and summarizing dashboards, managing datasources, and running queries against Prometheus and Loki, all with explicit context window management. Additional features include incident management and Sift investigation retrieval.

• ⭐ 1,850
• MCP
• grafana/mcp-grafana

Edge Delta MCP Server is a Model Context Protocol server enabling advanced integration with Edge Delta APIs. It allows developers and tools to extract, analyze, and automate observability data from Edge Delta through standardized MCP interfaces. The server supports AI-powered applications and automations, and can be deployed via Docker for straightforward operation. The Go API is available for experimental programmatic access.

• ⭐ 5
• MCP
• edgedelta/edgedelta-mcp-server

Signoz MCP Server acts as a bridge between SigNoz observability platforms and AI assistants by implementing the Model Context Protocol (MCP). It exposes a suite of tools for querying dashboard information, fetching panel and metrics data, executing custom queries, and retrieving traces or logs from SigNoz. The tool supports integration with popular AI assistants, flexible deployment options (Docker, local virtual environments), and secure configuration via environment variables or YAML files. The server is designed to enable standardized programmatic context retrieval for enhancing AI/LLM workflows.

• ⭐ 11
• MCP
• DrDroidLab/signoz-mcp-server

VictoriaLogs MCP Server implements the Model Context Protocol (MCP) to provide seamless, read-only integration with VictoriaLogs instances. It enables comprehensive access to VictoriaLogs APIs, allowing for log querying, exploration, and advanced observability tasks. The server includes embedded and searchable documentation and supports automation and interaction capabilities via standardized MCP tools. Designed to combine with other MCP servers, it enhances engineering workflows for log analysis and troubleshooting.

• ⭐ 30
• MCP
• VictoriaMetrics-Community/mcp-victorialogs

MCP Toolbox for Databases is an open source server that implements the Model Context Protocol (MCP) for database interactions in Gen AI workflows. It manages core complexities such as connection pooling, authentication, and tool integration, enabling developers to create and deploy database tools with ease and enhanced security. The toolbox supports streamlined connections between development environments and databases, offering observability, context-aware code generation, and automation features. Its design emphasizes rapid integration, reusable tools, and compatibility with AI assistants.

• ⭐ 11,412
• MCP
• googleapis/genai-toolbox