MCP server that allows interaction with PocketBase databases, enabling record operations (fetch, list, create, update), file management, and schema migrations through natural language.
A multi-agent MCP server that turns LLMs into an autonomous incident-response copilot, enabling rapid investigation, correlation, and remediation of production incidents.
An MCP server that enables users to transform AI conversations into a structured, searchable knowledge base by saving ideas, code snippets, bookmarks, and reminders. It supports persistent storage through Supabase or PostgreSQL and includes webhook integrations for automating workflows with external tools.
MCP server integrating with PocketBase to manage tasks and projects. Enables AI models to create tasks, list tasks with status filters, and browse projects.
An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.
MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.