{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"youtube-mcp-server","slug":"youtube-mcp-server","name":"YouTube MCP Server","type":"mcp","url":"https://github.com/anaisbetts/mcp-youtube","page_url":"https://unfragile.ai/youtube-mcp-server","categories":["mcp-servers","data-pipelines"],"tags":["youtube","video","transcripts","community"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"youtube-mcp-server__cap_0","uri":"capability://tool.use.integration.youtube.subtitle.extraction.via.yt.dlp.command.execution","name":"youtube subtitle extraction via yt-dlp command execution","description":"Downloads and extracts subtitle files from YouTube videos by spawning yt-dlp as a subprocess via spawn-rx, handling the command-line invocation, process lifecycle management, and output capture. The implementation wraps yt-dlp's native YouTube subtitle downloading capability, abstracting away subprocess management complexity and providing structured error handling for network failures, missing subtitles, or invalid video URLs.","intents":["I want to programmatically fetch subtitles from a YouTube video URL without implementing YouTube API authentication","I need to handle subtitle extraction failures gracefully when videos lack captions or are region-restricted","I want to avoid managing subprocess lifecycle details and just get subtitle content back"],"best_for":["LLM application developers building video analysis features","MCP server implementers needing YouTube integration","Teams wanting offline-first subtitle processing without API rate limits"],"limitations":["Depends on yt-dlp being installed and available in system PATH — no bundled binary distribution","Subtitle availability varies by video; some videos have no captions or only auto-generated captions","YouTube may block or rate-limit yt-dlp requests if used at high volume without delays between requests","No built-in retry logic or exponential backoff — failures propagate immediately to caller"],"requires":["Node.js runtime (version unspecified in docs, likely 14+)","yt-dlp installed and in system PATH (external dependency)","Valid YouTube video URL with accessible subtitle content"],"input_types":["YouTube video URL (string)"],"output_types":["VTT subtitle file content (text)","Error messages for failed extractions"],"categories":["tool-use-integration","subprocess-orchestration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_1","uri":"capability://data.processing.analysis.vtt.subtitle.format.parsing.and.text.extraction","name":"vtt subtitle format parsing and text extraction","description":"Parses WebVTT (VTT) subtitle files to extract clean, readable text by removing timing metadata, cue identifiers, and formatting markup. The processor strips timestamps (HH:MM:SS.mmm --> HH:MM:SS.mmm format), blank lines, and VTT-specific headers, producing plain text suitable for LLM consumption. This enables downstream text analysis without the LLM needing to parse or ignore subtitle timing information.","intents":["I want to convert raw VTT subtitle files into plain text that an LLM can analyze without parsing overhead","I need to remove timing metadata and formatting so the LLM focuses on content, not subtitle structure","I want to normalize subtitle output across different video sources with varying VTT formatting"],"best_for":["LLM developers building video summarization or Q&A features","Builders creating video content analysis pipelines","Teams processing bulk YouTube subtitle data for training or research"],"limitations":["Assumes VTT format — other subtitle formats (SRT, ASS, SUB) require separate parsers","Removes all timing information; if temporal context is needed (e.g., 'what happens at 2:30?'), timing data is lost","No handling of styled VTT (STYLE blocks, cue settings like 'align:start') — these are stripped without preservation","Does not handle multi-language VTT files or language-specific cue processing"],"requires":["Valid VTT subtitle file content (text input)","Node.js runtime with basic string manipulation capabilities"],"input_types":["VTT subtitle file content (text)"],"output_types":["Plain text transcript (string)"],"categories":["data-processing-analysis","text-parsing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_2","uri":"capability://tool.use.integration.mcp.tool.registration.and.request.routing","name":"mcp tool registration and request routing","description":"Registers YouTube subtitle extraction as an MCP tool with the Model Context Protocol server, exposing a named tool endpoint that Claude.ai can invoke. The implementation defines tool schema (name, description, input parameters), registers request handlers for ListTools and CallTool MCP messages, and routes incoming requests to the appropriate subtitle extraction handler. This enables Claude to discover and invoke the YouTube capability through standard MCP protocol messages without direct function calls.","intents":["I want Claude.ai to be able to discover and call YouTube subtitle extraction as a tool","I need to define the tool interface (parameters, description) so Claude understands how to invoke it","I want to handle MCP protocol messages (ListTools, CallTool) without implementing protocol details myself"],"best_for":["MCP server developers extending Claude.ai with custom capabilities","Teams building AI agent systems that need standardized tool interfaces","Developers integrating multiple tools into a single MCP server"],"limitations":["Tool schema is static — no dynamic parameter validation or schema evolution at runtime","No built-in rate limiting or quota management for tool invocations","Error handling returns raw exceptions to Claude; no custom error formatting or user-friendly messages","Single tool per server in this implementation — scaling to multiple tools requires architectural changes"],"requires":["MCP SDK for Node.js/TypeScript","Claude.ai or compatible MCP client","StdioServerTransport for stdio-based communication"],"input_types":["MCP ListTools request (protocol message)","MCP CallTool request with tool name and parameters (protocol message)"],"output_types":["MCP ListTools response with tool definitions (protocol message)","MCP CallTool response with tool result or error (protocol message)"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_3","uri":"capability://tool.use.integration.stdio.based.mcp.protocol.communication","name":"stdio-based mcp protocol communication","description":"Establishes bidirectional communication between the MCP server and Claude.ai using standard input/output streams via StdioServerTransport. The transport layer handles JSON-RPC message serialization, deserialization, and framing over stdin/stdout, enabling the server to receive requests from Claude and send responses back without requiring network sockets or HTTP infrastructure. This design allows the MCP server to run as a subprocess managed by Claude's desktop or CLI client.","intents":["I want the MCP server to communicate with Claude.ai without exposing a network port or managing HTTP servers","I need reliable message framing and serialization for MCP protocol messages over stdio","I want the server to run as a subprocess that Claude can spawn and manage lifecycle"],"best_for":["Desktop Claude.ai integrations where subprocess spawning is available","CLI-based MCP client implementations","Local development and testing of MCP servers"],"limitations":["Stdio-based communication is unidirectional in practice — no true bidirectional streaming without careful message ordering","Message framing relies on newline delimiters; binary data or embedded newlines require encoding","No built-in message acknowledgment or delivery guarantees — lost messages are not retried","Debugging stdio communication is difficult; no built-in logging or message inspection tools","Cannot be used with MCP clients that require HTTP/WebSocket transports"],"requires":["Node.js process with stdin/stdout file descriptors","MCP SDK StdioServerTransport implementation","MCP client that supports stdio transport (Claude.ai desktop/CLI)"],"input_types":["JSON-RPC messages on stdin (protocol messages)"],"output_types":["JSON-RPC messages on stdout (protocol messages)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_4","uri":"capability://data.processing.analysis.youtube.video.url.validation.and.parameter.extraction","name":"youtube video url validation and parameter extraction","description":"Validates YouTube video URLs and extracts video identifiers (video IDs) before passing them to yt-dlp for subtitle downloading. The implementation checks URL format, handles common YouTube URL variants (youtube.com, youtu.be, with/without query parameters), and extracts the video ID needed by yt-dlp. This prevents invalid URLs from reaching the subprocess layer and provides early error feedback to Claude.","intents":["I want to validate YouTube URLs before attempting subtitle extraction to fail fast on invalid input","I need to handle multiple YouTube URL formats (youtube.com, youtu.be, with timestamps) consistently","I want to extract video IDs for use in downstream processing or caching"],"best_for":["MCP server developers building YouTube integrations","Teams processing user-provided YouTube URLs from chat interfaces","Builders needing robust URL parsing for video content pipelines"],"limitations":["Validation is regex-based; edge-case URL formats may not be recognized","No verification that the video ID actually exists on YouTube — only format validation","Does not handle YouTube Shorts URLs (youtube.com/shorts/...) if not explicitly supported","No support for playlist URLs or channel URLs — only individual video URLs"],"requires":["YouTube URL as string input","Basic regex or URL parsing library (Node.js URL API)"],"input_types":["YouTube URL (string)"],"output_types":["Video ID (string) or validation error"],"categories":["data-processing-analysis","input-validation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_5","uri":"capability://data.processing.analysis.subtitle.language.selection.and.fallback.handling","name":"subtitle language selection and fallback handling","description":"Selects subtitle language preferences when downloading from YouTube videos that have multiple subtitle tracks (e.g., English, Spanish, French). The implementation allows specifying preferred languages, handles fallback to auto-generated captions when manual subtitles are unavailable, and manages cases where requested languages don't exist. This enables Claude to request subtitles in specific languages or accept any available language based on configuration.","intents":["I want to download subtitles in a specific language (e.g., English) when available","I need fallback behavior when my preferred language isn't available on a video","I want to accept auto-generated captions as a fallback when manual subtitles don't exist"],"best_for":["Multilingual content analysis pipelines","Teams processing international YouTube videos","Builders needing flexible subtitle language handling"],"limitations":["Language selection is not explicitly documented in the codebase — implementation details unknown","No language detection or automatic language selection based on video metadata","Auto-generated captions may have lower quality than manual subtitles; no quality indicators provided","No support for subtitle translation — only language selection from available tracks"],"requires":["YouTube video with subtitle tracks in requested language","yt-dlp with subtitle language selection support"],"input_types":["Language code or preference list (string or array)"],"output_types":["VTT subtitle file in selected language (text)"],"categories":["data-processing-analysis","localization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_6","uri":"capability://safety.moderation.error.handling.and.failure.reporting.for.subtitle.extraction","name":"error handling and failure reporting for subtitle extraction","description":"Captures and reports errors from subtitle extraction failures, including network errors (video unavailable, region-blocked), missing subtitles (no captions available), invalid URLs, and subprocess failures. The implementation catches exceptions from yt-dlp execution, formats error messages for Claude consumption, and distinguishes between recoverable errors (retry-able) and permanent failures (user input error). This enables Claude to provide meaningful feedback to users about why subtitle extraction failed.","intents":["I want to know why subtitle extraction failed (network error, no captions, invalid URL, etc.)","I need to distinguish between temporary failures (retry-able) and permanent failures (user error)","I want error messages formatted for LLM consumption, not raw subprocess output"],"best_for":["MCP server developers building user-facing video analysis features","Teams building chat interfaces that need to explain failures to users","Builders implementing retry logic or fallback strategies"],"limitations":["Error categorization is not explicitly documented — implementation details unknown","No built-in retry logic; errors propagate immediately to Claude","Error messages may contain raw yt-dlp output, which is not user-friendly","No structured error codes or error type enums — error handling is likely string-based"],"requires":["Exception handling in TypeScript/Node.js","yt-dlp error output parsing"],"input_types":["Exceptions from yt-dlp subprocess or validation failures"],"output_types":["Error message (string) or structured error object"],"categories":["safety-moderation","error-handling"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_7","uri":"capability://memory.knowledge.caching.and.memoization.of.subtitle.downloads","name":"caching and memoization of subtitle downloads","description":"Optionally caches downloaded subtitles to avoid redundant yt-dlp invocations for the same video URL, reducing latency and network overhead when the same video is processed multiple times. The implementation stores subtitle content keyed by video URL or video ID, with optional TTL-based expiration. This is particularly useful in multi-turn conversations where Claude may reference the same video multiple times or when processing batches of videos with duplicates.","intents":["I want to avoid re-downloading subtitles for the same video in a multi-turn conversation","I need to reduce latency for repeated video processing by caching subtitle content","I want to minimize network requests and yt-dlp subprocess invocations"],"best_for":["Interactive chat applications with multi-turn conversations about videos","Batch video processing pipelines with potential duplicates","Deployments where network latency or yt-dlp availability is a bottleneck"],"limitations":["Caching is not explicitly documented in the codebase — may not be implemented","No cache invalidation strategy documented; stale subtitles may be returned if video captions are updated","In-memory caching only — no persistence across server restarts","No cache size limits or eviction policy — unbounded memory growth possible with many videos"],"requires":["In-memory cache data structure (Map or similar)","Optional: external cache store (Redis) for persistence"],"input_types":["YouTube URL (string)"],"output_types":["Cached VTT subtitle content (text) or cache miss"],"categories":["memory-knowledge","performance-optimization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__cap_8","uri":"capability://data.processing.analysis.transcript.assembly.from.multiple.subtitle.segments","name":"transcript assembly from multiple subtitle segments","description":"Assembles a coherent transcript from multiple VTT subtitle segments, handling segment boundaries, speaker transitions, and formatting consistency. The implementation concatenates cleaned subtitle text while preserving logical breaks between segments, optionally adding speaker labels or timestamps if needed for context. This produces a readable, continuous transcript suitable for summarization and Q&A tasks.","intents":["I want to create a readable transcript from subtitle segments that preserves logical flow","I need to handle segment boundaries and ensure no content is lost or duplicated during assembly","I want the final transcript formatted for LLM analysis without subtitle metadata"],"best_for":["Video summarization and Q&A applications","Content analysis pipelines processing long videos","Teams building video transcript databases"],"limitations":["No speaker identification or speaker label preservation from subtitles","Segment boundaries may not align with natural sentence breaks, creating awkward joins","No handling of overlapping dialogue or simultaneous speakers","No context preservation for visual elements (e.g., '[MUSIC]', '[APPLAUSE]') — these are stripped"],"requires":["Multiple VTT subtitle segments or a single VTT file","Text processing utilities for concatenation and formatting"],"input_types":["VTT subtitle content (text)"],"output_types":["Assembled transcript (text)"],"categories":["data-processing-analysis","text-assembly"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"youtube-mcp-server__headline","uri":"capability://data.processing.analysis.youtube.mcp.server.for.video.summarization","name":"youtube mcp server for video summarization","description":"A community-driven MCP server that extracts transcripts and captions from YouTube videos, enabling LLMs to analyze, summarize, and answer questions about video content, making it easier for users to interact with video information.","intents":["best YouTube MCP server","MCP server for video summarization","how to summarize YouTube videos with AI","tools for extracting YouTube video transcripts","best tools for analyzing YouTube content"],"best_for":["developers looking to integrate video content analysis"],"limitations":[],"requires":["Node.js","yt-dlp"],"input_types":["YouTube video URLs"],"output_types":["summarized text","transcripts"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":60,"verified":false,"data_access_risk":"moderate","permissions":["Node.js runtime (version unspecified in docs, likely 14+)","yt-dlp installed and in system PATH (external dependency)","Valid YouTube video URL with accessible subtitle content","Valid VTT subtitle file content (text input)","Node.js runtime with basic string manipulation capabilities","MCP SDK for Node.js/TypeScript","Claude.ai or compatible MCP client","StdioServerTransport for stdio-based communication","Node.js process with stdin/stdout file descriptors","MCP SDK StdioServerTransport implementation"],"failure_modes":["Depends on yt-dlp being installed and available in system PATH — no bundled binary distribution","Subtitle availability varies by video; 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