hex-dashboard-mcp
Related Servers
Alternatives to hex-dashboard-mcp
No user-submitted related servers found.
Related Servers
- AlicenseBqualityDmaintenanceMCP server for managing Claude Code conversation sessions1260MIT
- FlicenseNot gradedqualityAmaintenanceMCP server for programmatic lifecycle management of Claude Code sessions, supporting list, create, read, send, fork, wait, and interrupt operations.31-
- AlicenseBqualityDmaintenanceA Model Context Protocol (MCP) server that provides comprehensive Jupyter notebook interaction capabilities, compatible with Claude Code.296MIT
- AlicenseAqualityAmaintenanceAn MCP server for managing Modal — apps, containers, volumes, and secrets — and for deploying & running Modal apps directly from Claude Code and other MCP clients.122MIT
- AlicenseAqualityBmaintenanceCode intelligence MCP server for Claude Code providing multi-project code graph, semantic search, session history, knowledge base, and web search.153MIT
- FlicenseNot gradedqualityFmaintenanceAn MCP server for coordinating multiple Claude Code sessions across related projects.-
TDQS
Scored across 18 tools
Most tools have clear, distinct purposes: project listing, cell editing, run management, and chart injection. Some overlap exists between run_project and run_and_wait (both trigger runs), and between diagnose_notebook and inspect_filter_behavior (both diagnose issues), but descriptions clarify the differences well.
All tool names follow the verb_noun pattern in snake_case (e.g., get_design_system, list_projects, update_cell_source, cancel_run). The consistent style makes the API predictable and easy to navigate.
With 18 tools, the server is slightly heavy but still scoped appropriately for a dashboard/notebook MCP. Each tool covers a distinct aspect of the workflow, though a few (diagnostics and run variants) could potentially be consolidated without losing functionality.
The tool set covers the full cell lifecycle (read, create, update, delete), run management (trigger, poll, cancel, history), and common dashboard visualization injection (Plotly, PyDeck, HTML). Minor gaps include lack of project create/delete and no explicit cell listing tool (only via get_project), but these are workable.