A
licenseA
qualityD
maintenanceMulti-provider AI video, speech, music, and transcription MCP server enabling video generation, image-to-video, TTS, music creation, and speech-to-text via a unified interface.
3
MIT
Replicate-MCP-Server
by sena-labs
Related Servers
Alternatives to Replicate-MCP-Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceA self-hosted MCP server that connects AI clients to local media-generation backends like ComfyUI and Blender, and provides built-in utilities for video/audio analysis, editing, subtitles, speech, and scene detection via a persistent file cache.1Apache 2.0
- AlicenseAqualityFmaintenanceProduction-grade MCP server for image and video understanding and generation across Gemini, OpenAI, and Grok.5171 PyPI4Apache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients to generate images and videos, synthesize text-to-speech audio, and clone or design custom voices. It also supports flexible output handling (URLs or local files) and multiple transport modes including stdio, REST, and SSE.188 npmMIT
- AlicenseAqualityCmaintenanceMulti-provider media generation MCP server that generates images, videos, audio, and transcriptions from text prompts using OpenAI, xAI, Gemini, ElevenLabs, and BFL through a single unified interface.632 npm2MIT
- AlicenseNot gradedqualityBmaintenanceEnables any MCP client to search and submit tasks across 350+ multimodal image, video, audio, and 3D models, run ComfyUI workflows and AI apps, upload/download files, and chat with LLMs. It supports stdio MCP integration and optional scope trimming for image, video, or audio only.2MIT
TDQS
A3.8/5.0
Scored across 36 tools
Disambiguation3/5
Most tools target distinct actions (generate image/video/audio, upscale, inpaint, train, deploy), but replicate_run_model is a generic escape hatch that overlaps every specialized generation tool, and its examples duplicate curated tools like upscale and remove-background. The two async multi-run tools, replicate_pipeline_start and replicate_batch_start, are related enough to require careful reading despite their descriptions.
Naming Consistency4/5
Almost all tools use a snake_case replicate_ prefix with readable verb/noun ordering. Minor deviations exist: some tools put the noun first (replicate_pipeline_start, replicate_batch_status), and a few are single verbs/nouns (replicate_chat, replicate_vision, replicate_inpaint, replicate_segment, replicate_lipsync).
Tool Count2/5
36 tools is well above the recommended 3-15 range and feels heavy even for a broad Replicate platform. The surface includes many specialized generation tools, asynchronous job management, training/deployment management, and discovery utilities, making it harder to scan and increasing overlap risk.
Completeness4/5
Coverage is strong across media generation, generic model execution, schema inspection, predictions, batches, pipelines, trainings, deployments, file upload, and model discovery. Minor gaps remain around deployment lifecycle management (list/get/run exist, but create/update/delete are absent) and file management beyond upload.
Maintenance
ActivityMaintained
ResponsivenessResponsive