A Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.
A Model Context Protocol (MCP) server that provides safe, read-only access to Kubernetes resources for debugging and inspection. Built with security in mind, it offers comprehensive cluster visibility without modification capabilities.
Enables interaction with Datadog's monitoring and observability platform through the MCP protocol. Supports incident management, monitor status checks, log searches, metrics queries, APM traces, dashboard access, RUM analytics, host management, and downtime scheduling.
Enables large language models to directly access and search content in ZIM files, allowing offline question answering and information retrieval from resources like Wikipedia.
Provides Kanban, Gantt, list views, multi-project management, and archiving for task management via MCP protocol, enabling Cherry Studio Agent to create, update, query, and organize tasks.
Provides AI assistants with persistent graph-based memory capabilities using Neo4j, enabling semantic search, relationship tracking, and knowledge organization across multiple project contexts.
Universal documentation knowledge-graph MCP server with hybrid full-text + vector search. Indexes local files and remote sources from Notion, Jira, Obsidian, Linear, GitHub, and Confluence into a single SQLite knowledge graph, exposing it to AI agents via the Model Context Protocol.
A demonstration implementation of a Model Context Protocol server that provides simple mathematical tools (add, subtract) and personalized greeting resources.
Enables AI assistants to fully interact with Odoo ERP instances over XML-RPC, supporting read and write operations on any model without requiring Odoo module installation.
