@mudravaorg/mcp-server
Related Servers
Alternatives to @mudravaorg/mcp-server
No user-submitted related servers found.
Related Servers
- FlicenseAqualityDmaintenanceAn MCP server that enables AI coding agents to create pixel art programmatically by providing canvas manipulation tools and PNG export.1017 npm2-
- AlicenseBqualityAmaintenanceAn MCP server that connects AI assistants to the PixelLab pixel art generation API. Generate sprites, tilesets, characters, animations, and more directly from Claude, Cursor, or any MCP-compatible client.103254 npm1MIT
- AlicenseNot gradedqualityFmaintenanceMCP server for generating style-consistent pixel art assets from PixelLab API, with project management, asset review, and an embedded Claude assistant.MIT
- AlicenseBqualityFmaintenanceAn MCP server that provides a database-backed kanban board with 40+ tools for AI agents to track issues, features, todos, epics, and diary entries across projects, including status workflows, relationships, and semantic search.4583MIT
- AlicenseCqualityDmaintenanceMCP server for Plane integration, enabling AI agents to interact with Plane APIs and services for project management tasks.100MIT
- AlicenseNot gradedqualityDmaintenanceMCP server for programmatically creating and editing Aseprite sprites, enabling AI agents to draw, manage layers and frames, and iterate until the desired result is achieved.MIT
TDQS
Scored across 26 tools
Most tools map to distinct actions/resources, but get_project's description already includes GitHub connection info, overlapping with get_github_context; list_tasks and list_ai_queue also require careful reading. The batch variants are clearly labeled as bulk versions, reducing confusion.
All tools use a consistent lowercase snake_case verb_noun pattern such as init_session, list_tasks, complete_ai_task, and batch_get_tasks. The pattern is predictable across session, task, comment, and GitHub operations.
At 26 tools, the server exceeds the 25-tool threshold and feels heavy. Several batch_* variants add redundant surface area that could be handled with optional parameters on the singular tools.
The core lifecycle is well covered: session/context setup, task CRUD and search, comments, kanban states, AI queue handling, GitHub file browsing, and PR creation/commit. Minor gaps such as deleting tasks, updating comments, or checking PR status are workarounds rather than dead ends.