{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-minimax-ai-minimax-mcp","slug":"mcp-minimax-ai-minimax-mcp","name":"MiniMax-MCP","type":"mcp","url":"https://github.com/MiniMax-AI/MiniMax-MCP","page_url":"https://unfragile.ai/mcp-minimax-ai-minimax-mcp","categories":["mcp-servers"],"tags":["image-generation","image-to-video","mcp","mcp-server","mcp-tools","text-to-image","text-to-speech","text-to-video","video-generation","voice-cloning"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-minimax-ai-minimax-mcp__cap_0","uri":"capability://text.generation.language.mcp.standardized.text.to.speech.synthesis.with.voice.selection","name":"mcp-standardized text-to-speech synthesis with voice selection","description":"Converts text input to audio output using MiniMax's text-to-audio API, exposed through the MCP protocol via a @mcp.tool decorated function. The server handles parameter marshaling, API authentication via region-specific endpoints (global vs mainland China), and returns either direct URLs or downloads audio files locally based on MINIMAX_API_RESOURCE_MODE configuration. Supports voice selection from a pre-defined voice list retrieved via list_voices tool.","intents":["I want to generate speech from text within my Claude Desktop or Cursor workflow without building custom API integration","I need to synthesize audio with specific voice characteristics for accessibility or content generation","I want to cache or locally store generated audio files instead of relying on temporary URLs"],"best_for":["AI agent builders using Claude Desktop or Cursor who need voice output capabilities","Teams building multi-modal applications that require TTS without direct API management","Developers in mainland China requiring regional API endpoint support"],"limitations":["Voice selection is limited to MiniMax's pre-defined voice list — no custom voice training without voice_clone capability","Audio generation is asynchronous and may introduce latency depending on MiniMax API response times","Local mode requires disk space and MINIMAX_MCP_BASE_PATH configuration; URL mode depends on MiniMax's CDN availability","No built-in audio streaming — entire audio file must be generated before playback"],"requires":["MiniMax API key (region-specific: global or mainland China)","Python 3.8+","MCP client integration (Claude Desktop, Cursor, Windsurf, or OpenAI Agents)","Network access to MiniMax API endpoints (https://api.minimaxi.chat or https://api.minimax.chat)"],"input_types":["text (plain string, max length dependent on MiniMax API limits)","voice_id (string identifier from list_voices output)"],"output_types":["audio file URL (default mode)","local audio file path (local mode, format: MP3 or WAV depending on API)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_1","uri":"capability://text.generation.language.voice.cloning.from.audio.samples.via.mcp","name":"voice cloning from audio samples via mcp","description":"Enables voice cloning by accepting audio file samples as input and generating a cloned voice model through MiniMax's voice_clone API. The server accepts audio files (WAV, MP3, or other formats supported by MiniMax), sends them to the API, and returns a voice_id that can be used with text_to_audio for subsequent synthesis. Implementation uses FastMCP's @mcp.tool decorator to expose the cloning function with parameter validation and error handling for malformed audio inputs.","intents":["I want to clone a specific voice from audio samples and reuse it for multiple TTS generations","I need to preserve a particular speaker's voice characteristics for personalized content generation","I want to create branded voice personas for my AI agent without manual voice talent recording"],"best_for":["Content creators building personalized AI agents with branded voice output","Teams generating multi-language content with consistent voice identity","Accessibility teams creating custom voices for specific user needs"],"limitations":["Voice cloning quality depends on input audio sample quality — noisy or low-fidelity samples produce poor clones","Cloning process may be rate-limited by MiniMax API; no built-in queue management for batch cloning","Cloned voice_ids are tied to the MiniMax account and API key — no cross-account voice sharing","No feedback mechanism to evaluate clone quality before using it in production TTS calls"],"requires":["MiniMax API key with voice cloning capability enabled","Audio file samples (minimum duration and quality requirements per MiniMax API docs)","Python 3.8+","MCP client (Claude Desktop, Cursor, etc.)"],"input_types":["audio files (WAV, MP3, or formats supported by MiniMax)","voice_name (string identifier for the cloned voice)"],"output_types":["voice_id (string identifier for the cloned voice, usable in text_to_audio calls)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_10","uri":"capability://tool.use.integration.fastmcp.based.tool.registration.and.parameter.validation","name":"fastmcp-based tool registration and parameter validation","description":"Leverages FastMCP framework's @mcp.tool decorator pattern to register tools with automatic parameter validation, type hints, and schema generation. Each tool (text_to_audio, generate_video, text_to_image, etc.) is defined as a Python function with type-annotated parameters, and FastMCP automatically generates JSON schemas for MCP clients. The framework handles parameter marshaling, type coercion, and validation errors, reducing boilerplate code and ensuring consistent tool interfaces across all capabilities.","intents":["I want to define MCP tools with automatic parameter validation without manual schema writing","I need consistent error handling and type checking across all generation tools","I want to expose Python functions as MCP tools with minimal boilerplate"],"best_for":["Python developers building MCP servers with FastMCP","Teams needing rapid tool development with automatic schema generation","Projects requiring consistent parameter validation across multiple tools"],"limitations":["FastMCP is a specific framework — switching to other MCP implementations requires rewriting tool definitions","Parameter validation is limited to type hints — complex validation logic must be implemented manually","Schema generation is automatic but may not capture all validation constraints (e.g., string length limits, regex patterns)","Error messages are framework-generated — limited customization for user-facing error handling"],"requires":["Python 3.8+","FastMCP framework (included in minimax_mcp dependencies)","Type hints for all tool parameters"],"input_types":[],"output_types":[],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_11","uri":"capability://tool.use.integration.client.integration.configuration.for.claude.desktop.and.cursor","name":"client integration configuration for claude desktop and cursor","description":"Provides documented configuration patterns for integrating the MCP server with Claude Desktop and Cursor via configuration files. For Claude Desktop, the server is configured in the Claude configuration JSON file with stdio transport and Python executable path. For Cursor, configuration is added through Cursor Settings > MCP > Add new global MCP Server. The server abstracts integration details, enabling clients to add the server without understanding MCP protocol internals. Configuration includes API key and region settings passed as environment variables.","intents":["I want to integrate the MiniMax MCP server with Claude Desktop for text-to-speech and image generation","I need to configure the MCP server in Cursor to access MiniMax generation capabilities","I want to set up the server with minimal configuration complexity"],"best_for":["Claude Desktop and Cursor users wanting MiniMax generation capabilities","Teams standardizing on Claude Desktop or Cursor for AI workflows","Developers unfamiliar with MCP protocol needing guided integration"],"limitations":["Configuration is client-specific — separate setup required for Claude Desktop, Cursor, Windsurf, and OpenAI Agents","Configuration files are JSON/YAML — no UI-based configuration wizard","API keys must be set as environment variables — no secure credential storage integration","Configuration changes require client restart — no hot-reload support","Documentation may lag behind client UI changes (Claude Desktop, Cursor versions)"],"requires":["Claude Desktop or Cursor installed","MiniMax API key","Python 3.8+ installed and in PATH","Access to client configuration files (Claude Desktop: ~/.claude/claude_desktop_config.json, Cursor: settings)"],"input_types":[],"output_types":[],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_2","uri":"capability://image.visual.text.to.image.generation.with.prompt.based.synthesis","name":"text-to-image generation with prompt-based synthesis","description":"Generates images from text prompts using MiniMax's image generation API, exposed via MCP @mcp.tool decorator. The server accepts a text prompt, sends it to MiniMax's image generation endpoint, and returns either a URL to the generated image (default) or downloads it locally based on MINIMAX_API_RESOURCE_MODE. Supports region-specific API routing and handles image format negotiation with the backend API.","intents":["I want to generate images from text descriptions within my Claude Desktop workflow for content creation","I need to create visual assets programmatically without using separate image generation tools","I want to batch-generate images and store them locally for offline use or compliance reasons"],"best_for":["Content creators using Claude Desktop or Cursor for rapid visual asset generation","AI agent builders needing image generation as part of multi-modal workflows","Teams in mainland China requiring regional API compliance"],"limitations":["Image generation quality and diversity depend on MiniMax's model capabilities — no fine-tuning or style control parameters exposed","Generation latency can be 5-30 seconds depending on MiniMax API load; no progress callbacks or streaming updates","URL mode returns temporary URLs with expiration; local mode requires disk space and MINIMAX_MCP_BASE_PATH configuration","No built-in image editing or post-processing — only raw generation from prompts"],"requires":["MiniMax API key with image generation capability","Python 3.8+","MCP client (Claude Desktop, Cursor, Windsurf, OpenAI Agents)","Network access to MiniMax API endpoints"],"input_types":["text prompt (string describing desired image)"],"output_types":["image URL (default mode, typically PNG or JPEG)","local image file path (local mode)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_3","uri":"capability://image.visual.text.to.video.generation.with.prompt.based.synthesis","name":"text-to-video generation with prompt-based synthesis","description":"Generates videos from text prompts using MiniMax's video generation API, exposed via MCP @mcp.tool decorator. The server accepts a text prompt describing desired video content, sends it to MiniMax's video generation endpoint, and returns either a URL to the generated video or downloads it locally. Handles region-specific API routing and manages video file format negotiation with the backend. Video generation is asynchronous and may require polling or callback mechanisms for completion status.","intents":["I want to generate short videos from text descriptions for content creation or marketing","I need to create visual demos or product videos programmatically without video editing software","I want to batch-generate videos and store them locally for offline distribution or compliance"],"best_for":["Content creators using Claude Desktop for rapid video asset generation","Marketing teams building AI-powered video generation workflows","AI agent builders needing video output for multi-modal applications"],"limitations":["Video generation is computationally expensive — generation latency typically 30-120 seconds or longer","No progress tracking or streaming — entire video must complete before URL/file is available","Video quality and length constraints depend on MiniMax API limits (resolution, duration, frame rate)","Local mode requires significant disk space for video files; URL mode depends on MiniMax CDN availability and expiration","No built-in video editing or post-processing — only raw generation from prompts"],"requires":["MiniMax API key with video generation capability","Python 3.8+","MCP client (Claude Desktop, Cursor, Windsurf, OpenAI Agents)","Network access to MiniMax API endpoints","Sufficient disk space if using local mode (videos typically 50-500MB)"],"input_types":["text prompt (string describing desired video content)"],"output_types":["video URL (default mode, typically MP4 or WebM)","local video file path (local mode)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_4","uri":"capability://image.visual.image.to.video.synthesis.from.static.images","name":"image-to-video synthesis from static images","description":"Generates videos from static image inputs using MiniMax's image-to-video API, exposed via MCP @mcp.tool decorator. The server accepts an image file (PNG, JPEG, or other formats), optionally a text prompt for motion guidance, sends them to MiniMax's image-to-video endpoint, and returns either a URL or local file path to the generated video. Handles image encoding, region-specific API routing, and asynchronous video generation with completion status handling.","intents":["I want to animate static images into short videos for content creation or social media","I need to create motion sequences from product photos or artwork without video production tools","I want to generate multiple video variations from a single image with different motion prompts"],"best_for":["Content creators and marketers generating animated assets from static images","E-commerce teams creating product videos from catalog images","AI agent builders needing image-to-video capabilities for multi-modal workflows"],"limitations":["Video generation latency is significant (30-120+ seconds) — not suitable for real-time applications","Motion quality depends on image quality and prompt specificity — low-resolution or ambiguous images produce poor results","No streaming or progress tracking — entire video must complete before output is available","Video length and resolution constraints depend on MiniMax API limits","Local mode requires substantial disk space; URL mode depends on CDN availability and expiration"],"requires":["MiniMax API key with image-to-video capability","Image file (PNG, JPEG, or formats supported by MiniMax)","Python 3.8+","MCP client (Claude Desktop, Cursor, Windsurf, OpenAI Agents)","Network access to MiniMax API endpoints"],"input_types":["image file (PNG, JPEG, or other formats)","motion prompt (optional text string describing desired motion)"],"output_types":["video URL (default mode, typically MP4 or WebM)","local video file path (local mode)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_5","uri":"capability://tool.use.integration.voice.list.enumeration.and.discovery","name":"voice list enumeration and discovery","description":"Exposes MiniMax's available voices through a list_voices MCP tool that returns a structured list of voice identifiers, names, and metadata. The server queries MiniMax's voice catalog API and caches or returns the results in real-time. This enables clients to discover available voices for text_to_audio synthesis without hardcoding voice IDs, supporting dynamic voice selection in Claude Desktop and Cursor workflows.","intents":["I want to discover what voices are available for text-to-speech synthesis","I need to programmatically select voices based on language, gender, or other characteristics","I want to display voice options to users in my AI agent interface"],"best_for":["AI agent builders needing dynamic voice selection UI","Teams building multi-language TTS applications","Developers integrating MiniMax TTS without hardcoding voice IDs"],"limitations":["Voice list is static per MiniMax API version — no real-time voice updates without server restart","No voice metadata beyond ID and name (e.g., no language, gender, or accent tags in response)","Caching strategy is not specified — repeated calls may hit the API or return stale data","Voice availability may vary by region (global vs mainland China API endpoints)"],"requires":["MiniMax API key","Python 3.8+","MCP client (Claude Desktop, Cursor, Windsurf, OpenAI Agents)","Network access to MiniMax API endpoints"],"input_types":[],"output_types":["structured list of voice objects (voice_id, voice_name, and optional metadata)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_6","uri":"capability://tool.use.integration.local.audio.playback.via.mcp","name":"local audio playback via mcp","description":"Provides a play_audio MCP tool that plays audio files locally on the client machine. The server accepts an audio file path or URL, handles audio format detection, and invokes the system audio player (or embedded player) to play the audio. This enables immediate audio playback of generated TTS or cloned voices within Claude Desktop or Cursor workflows without requiring external audio applications.","intents":["I want to preview generated speech immediately after synthesis","I need to play audio files within my Claude Desktop workflow without opening external players","I want to test voice cloning results before using them in production"],"best_for":["Content creators previewing TTS output in real-time","Voice cloning workflows requiring immediate quality assessment","AI agent builders needing audio playback for user feedback"],"limitations":["Playback is local to the MCP server machine — not suitable for remote client playback","Audio format support depends on system audio player capabilities — may fail on unsupported formats","No playback controls (pause, seek, volume) exposed through MCP interface","Blocking playback may delay MCP server response — no asynchronous playback option","Requires audio hardware and system audio configuration on the server machine"],"requires":["Audio file (local path or URL)","Python 3.8+","System audio player (ffplay, mpv, or platform-specific player)","Audio hardware on the MCP server machine"],"input_types":["audio file path (local filesystem path)","audio URL (HTTP/HTTPS URL to audio file)"],"output_types":["playback status (success/failure confirmation)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_7","uri":"capability://automation.workflow.dual.mode.resource.handling.url.vs.local.storage","name":"dual-mode resource handling (url vs local storage)","description":"Implements a configurable resource handling system via MINIMAX_API_RESOURCE_MODE environment variable that switches between URL mode (returns CDN URLs to generated resources) and local mode (downloads resources to MINIMAX_MCP_BASE_PATH). The server abstracts resource delivery, enabling clients to choose between cloud-hosted URLs (faster, no storage overhead) or local files (offline access, data residency compliance). This is implemented at the server level and applies to all generation tools (text-to-audio, text-to-image, text-to-video, image-to-video).","intents":["I want to store generated assets locally for offline use or data residency compliance","I need to avoid dependency on temporary CDN URLs that expire","I want to choose between cloud URLs and local storage based on deployment context"],"best_for":["Teams with data residency or compliance requirements (GDPR, CCPA, mainland China regulations)","Offline-first applications needing local asset storage","Enterprises avoiding external CDN dependencies"],"limitations":["Local mode requires disk space proportional to generated asset volume — no built-in cleanup or quota management","URL mode depends on MiniMax CDN availability and URL expiration — no guarantee of permanent URLs","Mode is global per server instance — cannot mix URL and local modes for different clients","No built-in asset lifecycle management (expiration, deletion, archival)","Local mode adds download latency after API generation completes"],"requires":["Environment variable MINIMAX_API_RESOURCE_MODE set to 'url' or 'local'","If local mode: MINIMAX_MCP_BASE_PATH environment variable pointing to writable directory","If local mode: sufficient disk space for generated assets","Python 3.8+"],"input_types":[],"output_types":["resource URL (URL mode)","local file path (local mode)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_8","uri":"capability://automation.workflow.region.aware.api.endpoint.routing","name":"region-aware api endpoint routing","description":"Implements region-specific API endpoint configuration via MINIMAX_API_REGION environment variable, routing requests to either global (https://api.minimaxi.chat) or mainland China (https://api.minimax.chat) API endpoints. The server abstracts regional routing, enabling single-codebase deployment across regions without hardcoding endpoints. API keys are region-specific and must match the configured endpoint. This routing is applied at the client initialization level and affects all API calls.","intents":["I want to deploy the MCP server to mainland China with compliant API endpoints","I need to switch between global and regional API endpoints based on deployment context","I want to avoid hardcoding region-specific endpoints in client code"],"best_for":["Teams deploying to mainland China requiring regional API compliance","Multi-region deployments needing environment-based endpoint configuration","Organizations with data residency requirements"],"limitations":["API keys are region-specific — using a global key with mainland China endpoint (or vice versa) will fail","Region is global per server instance — cannot serve multiple regions from a single server","No automatic region detection — region must be explicitly configured via environment variable","No fallback or failover between regions — misconfigured region results in API errors"],"requires":["Environment variable MINIMAX_API_REGION set to 'global' or 'cn' (or equivalent)","Region-specific MiniMax API key matching the configured endpoint","Python 3.8+"],"input_types":[],"output_types":[],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-minimax-ai-minimax-mcp__cap_9","uri":"capability://tool.use.integration.mcp.protocol.transport.abstraction.stdio.and.sse","name":"mcp protocol transport abstraction (stdio and sse)","description":"Implements transport-agnostic MCP server using FastMCP framework, supporting both stdio (standard input/output for local execution) and SSE (Server-Sent Events for network deployment). The server abstracts transport details, enabling the same tool definitions to work across different deployment contexts. Stdio transport is used for local Claude Desktop/Cursor integration, while SSE enables cloud or remote deployment. Transport selection is configured at server initialization and applies to all client communications.","intents":["I want to run the MCP server locally with Claude Desktop using stdio transport","I need to deploy the MCP server to a cloud environment accessible via network","I want to use the same server code for both local and remote deployments"],"best_for":["Developers integrating MCP server with Claude Desktop or Cursor locally","Teams deploying MCP server to cloud environments (AWS, GCP, Azure)","Organizations needing flexible deployment options (local vs remote)"],"limitations":["Stdio transport is limited to local execution — no network access","SSE transport requires HTTP server infrastructure — adds deployment complexity","Transport is global per server instance — cannot serve multiple transports simultaneously","Stdio transport may have buffering issues with large responses (videos, large audio files)","SSE transport requires proper CORS and authentication configuration for security"],"requires":["Python 3.8+","FastMCP framework (included in minimax_mcp dependencies)","For stdio: local process execution (Claude Desktop, Cursor, Windsurf)","For SSE: HTTP server and network connectivity"],"input_types":[],"output_types":[],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":48,"verified":false,"data_access_risk":"high","permissions":["MiniMax API key (region-specific: global or mainland China)","Python 3.8+","MCP client integration (Claude Desktop, Cursor, Windsurf, or OpenAI Agents)","Network access to MiniMax API endpoints (https://api.minimaxi.chat or https://api.minimax.chat)","MiniMax API key with voice cloning capability enabled","Audio file samples (minimum duration and quality requirements per MiniMax API docs)","MCP client (Claude Desktop, Cursor, etc.)","FastMCP framework (included in minimax_mcp dependencies)","Type hints for all tool parameters","Claude Desktop or Cursor installed"],"failure_modes":["Voice selection is limited to MiniMax's pre-defined voice list — no custom voice training without voice_clone capability","Audio generation is asynchronous and may introduce latency depending on MiniMax API response times","Local mode requires disk space and MINIMAX_MCP_BASE_PATH configuration; URL mode depends on MiniMax's CDN availability","No built-in audio streaming — entire audio file must be generated before playback","Voice cloning quality depends on input audio sample quality — noisy or low-fidelity samples produce poor clones","Cloning process may be rate-limited by MiniMax API; no built-in queue management for batch cloning","Cloned voice_ids are tied to the MiniMax account and API key — no cross-account voice sharing","No feedback mechanism to evaluate clone quality before using it in production TTS calls","FastMCP is a specific framework — switching to other MCP implementations requires rewriting tool definitions","Parameter validation is limited to type hints — complex validation logic must be implemented manually","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.4805259399793763,"quality":0.49,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:34.856Z","last_commit":"2026-04-15T07:03:02Z"},"community":{"stars":1459,"forks":257,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-minimax-ai-minimax-mcp","compare_url":"https://unfragile.ai/compare?artifact=mcp-minimax-ai-minimax-mcp"}},"signature":"E8BkMBO6IhbNZ/coRfM9D4sNOAVkeFyXvyJH6h7zXwcFf4HGaq9fEHr0MbXy27Nmlo2MtnZB9rh5Ls/oAg6CBQ==","signedAt":"2026-06-21T04:38:33.656Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-minimax-ai-minimax-mcp","artifact":"https://unfragile.ai/mcp-minimax-ai-minimax-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-minimax-ai-minimax-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}