{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-mureka","slug":"mureka","name":"Mureka","type":"mcp","url":"https://github.com/SkyworkAI/Mureka-mcp","page_url":"https://unfragile.ai/mureka","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-mureka__cap_0","uri":"capability://text.generation.language.lyric.generation.with.semantic.coherence","name":"lyric generation with semantic coherence","description":"Generates song lyrics by processing user prompts through a language model pipeline that maintains thematic consistency across verses, choruses, and bridges. The MCP server accepts lyric generation requests, routes them to configured LLM backends (OpenAI, Anthropic, or local models), and returns structured lyric content organized by song sections with metadata about rhyme scheme and emotional tone.","intents":["Generate original song lyrics from a concept or mood description","Create lyrics in specific genres or styles programmatically","Integrate lyric generation into music production workflows","Batch generate multiple lyric variations for A/B testing"],"best_for":["Music producers and songwriters building AI-assisted composition tools","Game developers needing procedural music content generation","Music streaming platforms implementing personalized content creation"],"limitations":["No built-in copyright detection or plagiarism checking against existing song catalogs","Lyric quality depends entirely on underlying LLM capability and prompt engineering","No native support for non-English languages without explicit model selection","Generated lyrics may lack cultural context or authentic genre-specific conventions"],"requires":["MCP client implementation (Claude Desktop, custom MCP host, or compatible tool)","API credentials for at least one LLM provider (OpenAI API key, Anthropic API key, or local Ollama instance)","Python 3.8+ runtime environment"],"input_types":["text prompt (lyric concept, mood, genre, style description)","structured JSON with song parameters (BPM, key, song structure)"],"output_types":["text (raw lyrics)","structured JSON (lyrics organized by section with metadata)"],"categories":["text-generation-language","music-generation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-mureka__cap_1","uri":"capability://planning.reasoning.song.composition.and.structure.planning","name":"song composition and structure planning","description":"Orchestrates the overall song creation workflow by decomposing user intent into discrete composition tasks: lyric generation, instrumental creation, and arrangement planning. The MCP server accepts high-level song briefs and returns a structured song composition plan with timing, section transitions, and instrumentation suggestions that can be executed sequentially or in parallel by downstream music generation tools.","intents":["Create a complete song structure plan from a single creative brief","Decompose song composition into parallel tasks for faster generation","Generate song arrangements with specific instrumentation and BPM","Plan song sections (intro, verse, chorus, bridge, outro) with timing"],"best_for":["Music production teams building end-to-end AI composition pipelines","Independent artists wanting structured composition assistance","Music education platforms teaching song structure and arrangement"],"limitations":["No real-time feedback loop — composition plan is static once generated","Cannot adapt to live performance constraints or studio limitations","Arrangement suggestions are generic without access to specific instrument libraries or DAW plugins","No validation against music theory rules or harmonic consistency"],"requires":["MCP client with multi-step task orchestration support","LLM with strong reasoning capabilities (GPT-4, Claude 3+, or equivalent)","Access to both lyric and instrumental generation endpoints"],"input_types":["text (song brief, mood, genre, target audience)","structured JSON (song parameters: BPM, key, duration, style)"],"output_types":["structured JSON (song composition plan with sections, timing, instrumentation)","text (human-readable song structure outline)"],"categories":["planning-reasoning","music-generation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-mureka__cap_2","uri":"capability://image.visual.instrumental.background.music.generation","name":"instrumental background music generation","description":"Generates background instrumental tracks (MIDI or audio) based on song parameters including genre, BPM, key, mood, and instrumentation preferences. The MCP server accepts instrumental generation requests and routes them to music generation models (e.g., MusicGen, Jukebox, or similar), returning audio files or MIDI sequences that can be imported into DAWs or used directly in compositions.","intents":["Generate royalty-free background music for songs in specific genres","Create instrumental variations with different instrumentation or arrangements","Produce MIDI sequences for further editing in DAWs","Generate multiple instrumental takes for A/B testing with lyrics"],"best_for":["Music producers needing rapid instrumental prototyping","Content creators building background music libraries","Game and film composers generating placeholder music for editing"],"limitations":["Generated audio quality depends on underlying music generation model (often lower fidelity than professional recordings)","No real-time parameter adjustment during generation — must regenerate for changes","Limited control over individual instrument performance or expression","MIDI output may require significant post-processing for musical authenticity","No guarantee of harmonic consistency with separately generated lyrics"],"requires":["MCP client with audio file handling support","Music generation model access (local MusicGen, API-based service, or equivalent)","Sufficient compute resources for audio generation (GPU recommended for quality)","Audio codec support for output formats (MP3, WAV, MIDI)"],"input_types":["structured JSON (genre, BPM, key, mood, duration, instrumentation list)","text (natural language description of desired instrumental style)"],"output_types":["audio file (MP3, WAV, or similar format)","MIDI sequence (for DAW import and editing)","structured metadata (instrumentation, timing, key information)"],"categories":["image-visual","music-generation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-mureka__cap_3","uri":"capability://tool.use.integration.multi.provider.llm.routing.for.music.generation","name":"multi-provider llm routing for music generation","description":"Routes music generation requests (lyrics, composition planning) to multiple LLM providers (OpenAI, Anthropic, local Ollama) based on availability, cost, or capability requirements. The MCP server maintains provider configurations, handles authentication, implements fallback logic when primary providers fail, and abstracts provider-specific API differences behind a unified interface.","intents":["Use different LLM providers for different generation tasks based on cost or capability","Implement fallback logic so generation continues if primary provider is unavailable","Switch between cloud and local models without changing client code","Optimize for latency by routing to fastest available provider"],"best_for":["Teams building production music generation systems requiring reliability","Cost-conscious developers wanting to optimize LLM provider selection","Organizations with multi-provider contracts or compliance requirements"],"limitations":["Fallback logic adds latency overhead (must detect provider failure before routing to backup)","No built-in load balancing across providers — uses simple sequential fallback","Provider-specific prompt optimization not automated; users must tune prompts per provider","No cost tracking or billing integration — users must monitor provider usage separately"],"requires":["API credentials for at least one LLM provider (OpenAI, Anthropic, or local Ollama)","MCP client with environment variable or configuration file support","Network connectivity to cloud providers or local Ollama instance"],"input_types":["structured JSON (provider preferences, fallback order, cost/latency constraints)","text (generation request with optional provider hints)"],"output_types":["text (generation result from selected provider)","structured JSON (result with provider metadata)"],"categories":["tool-use-integration","music-generation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-mureka__cap_4","uri":"capability://tool.use.integration.mcp.protocol.server.implementation.for.music.generation","name":"mcp protocol server implementation for music generation","description":"Implements the Model Context Protocol (MCP) server specification, exposing music generation capabilities (lyrics, instrumentals, composition planning) as standardized tools that can be called by MCP clients (Claude Desktop, custom agents, LLM frameworks). The server handles MCP message serialization/deserialization, tool schema definition, request routing, and response formatting according to MCP specification.","intents":["Integrate music generation into Claude Desktop or other MCP-compatible clients","Expose music generation as tools for LLM agents and autonomous workflows","Build music generation into custom MCP client applications","Compose music generation with other MCP tools in multi-tool workflows"],"best_for":["Developers building MCP-compatible music applications","Teams integrating music generation into Claude-based workflows","Organizations standardizing on MCP for tool composition"],"limitations":["MCP protocol overhead adds ~50-200ms latency per request compared to direct API calls","Requires MCP client implementation — cannot be used with standard REST API clients","Tool schema must be manually maintained in sync with underlying generation models","No built-in streaming support for long-running generation tasks"],"requires":["MCP client compatible with Mureka server (Claude Desktop 0.5+, custom MCP host, or framework with MCP support)","Python 3.8+ with MCP SDK dependencies","Network connectivity between MCP client and server (local or remote)"],"input_types":["MCP tool calls with JSON arguments (lyrics, instrumental, composition parameters)"],"output_types":["MCP tool results (JSON-formatted generation output)","MCP error responses with diagnostic information"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-mureka__cap_5","uri":"capability://data.processing.analysis.structured.song.metadata.extraction.and.formatting","name":"structured song metadata extraction and formatting","description":"Extracts and structures metadata from generated songs including section timing, instrumentation lists, key/BPM information, and lyrical themes. The server parses generation outputs and returns standardized JSON schemas containing song metadata that can be consumed by downstream tools (DAWs, music databases, recommendation systems) without additional parsing or transformation.","intents":["Extract song structure metadata for import into DAWs or music production tools","Generate searchable metadata for music database indexing","Create song summaries with key information for music discovery","Format generation outputs for integration with music management systems"],"best_for":["Music production platforms needing structured song data","Music discovery and recommendation systems","DAW plugins requiring standardized metadata formats"],"limitations":["Metadata extraction depends on LLM output format consistency — may fail with unexpected generation outputs","No validation against music theory standards or harmonic correctness","Limited to metadata extraction — does not validate or correct generation outputs","Schema is fixed and may not accommodate all music production use cases"],"requires":["Structured generation output from lyrics or instrumental generation","JSON schema validation library (included in standard Python)"],"input_types":["raw generation output (text or JSON from LLM)","structured JSON (partial metadata to be enriched)"],"output_types":["structured JSON (standardized song metadata schema)","text (human-readable song summary)"],"categories":["data-processing-analysis","music-generation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":25,"verified":false,"data_access_risk":"high","permissions":["MCP client implementation (Claude Desktop, custom MCP host, or compatible tool)","API credentials for at least one LLM provider (OpenAI API key, Anthropic API key, or local Ollama instance)","Python 3.8+ runtime environment","MCP client with multi-step task orchestration support","LLM with strong reasoning capabilities (GPT-4, Claude 3+, or equivalent)","Access to both lyric and instrumental generation endpoints","MCP client with audio file handling support","Music generation model access (local MusicGen, API-based service, or equivalent)","Sufficient compute resources for audio generation (GPU recommended for quality)","Audio codec support for output formats (MP3, WAV, MIDI)"],"failure_modes":["No built-in copyright detection or plagiarism checking against existing song catalogs","Lyric quality depends entirely on underlying LLM capability and prompt engineering","No native support for non-English languages without explicit model selection","Generated lyrics may lack cultural context or authentic genre-specific conventions","No real-time feedback loop — composition plan is static once generated","Cannot adapt to live performance constraints or studio limitations","Arrangement suggestions are generic without access to specific instrument libraries or DAW plugins","No validation against music theory rules or harmonic consistency","Generated audio quality depends on underlying music generation model (often lower fidelity than professional recordings)","No real-time parameter adjustment during generation — must regenerate for changes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.22,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"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":"2026-06-17T09:51:03.578Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mureka","compare_url":"https://unfragile.ai/compare?artifact=mureka"}},"signature":"fs+6ktmjRoqSXVFkrhYwLBqes2PNGVs40X8xHsM4Ewh0d26Nbufl0OKPo7pwMmMZ1CQ9KzHik2puK197yCXmCQ==","signedAt":"2026-06-22T13:19:31.310Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mureka","artifact":"https://unfragile.ai/mureka","verify":"https://unfragile.ai/api/v1/verify?slug=mureka","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"}}