A
licenseA
qualityB
maintenanceMCP server for AI-powered image, audio, and video generation, enabling media creation directly from Claude, Cursor, and other MCP clients.
11
41 npm
MIT
bumi-digital-mcp
by ezmakeai
Related Servers
Alternatives to bumi-digital-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceMCP server for AI-powered media generation: images, videos, audio, and upscaling using 99 AI models.6MIT
- AlicenseAqualityAmaintenanceGenerate AI images, video, voiceovers and music from Claude, Cursor or VS Code through 50+ models (Veo 3.1, Kling 3, Seedance, Nano Banana, GPT Image, ElevenLabs). Upload photos for edits and image-to-video. Tools are annotated (read-only vs. credit-spending); failed generations are refunded. Local via npx or hosted with OAuth at fattly.app.6101 npmMIT
- FlicenseNot gradedqualityCmaintenanceA Model Context Protocol server for AI image and video generation using Jimeng AI, enabling text-to-image, image composition, text-to-video, and image-to-video through Claude Desktop and other MCP clients.80-
- AlicenseBqualityCmaintenanceMCP server for generating images and audio using Google's Gemini AI models.22MIT
- AlicenseNot gradedqualityDmaintenanceMCP server for Higgsfield AI that enables image and video generation using 16+ models through Claude, Cursor, or any MCP-compatible client.220 npm3MIT
TDQS
A3.9/5.0
Scored across 11 tools
Disambiguation4/5
Most tools target distinct media types and actions clearly, but list_models and get_models_pricing overlap somewhat since both describe available models; the descriptions mitigate this by directing to get_models_pricing for details. There is also minor conceptual overlap between generate_video and generate_audio via lipsync, though the media type differs.
Naming Consistency5/5
All tool names follow a consistent lowercase snake_case verb_noun pattern: list_*, get_*, generate_*, upscale_*, check_*, upload_*. This makes the action and target easy to predict across the set.
Tool Count5/5
11 tools is well-scoped for an AI media generation API server. Each tool covers a necessary function: model discovery, generation across modalities, upscaling, status polling, history, credits, and file uploads.
Completeness4/5
The core generation lifecycle is well covered: list/get models, generate, poll status, view history, upload inputs, and check credits. Minor gaps exist such as no explicit cancel or delete generation/upload operations, but agents can complete normal workflows without dead ends.
Maintenance
ActivitySlowing
ResponsivenessNo issues