# Set-List Planner MCP > Set-List Planner optimizes live music performances by structuring your setlist based on energy dynamics and musical theory. Use this MCP to build a performance arc that builds tension, hits powerful climaxes, and accounts for vocal stamina. It analyzes key changes, tempo shifts, and overall song flow, ensuring your show feels engineered rather than just random tracks played back-to-back. ## Overview - **Category:** productivity - **Price:** Free - **Tags:** musician, setlist, live-performance, energy-curve, music-theory ## Description Building a great live setlist is an art form; it’s about managing energy. This MCP helps musicians do exactly that by mapping out the emotional curve of their performance. Instead of simply dumping songs onto a tracklist, you can structure your entire show to start strong, dip into a necessary mid-set pocket, and build toward a massive climax. You get deep analysis on how key changes or tempo jumps might sound—whether they'll feel jarring or totally natural. Furthermore, it helps you pull out crucial preparation details, like identifying the most common key in your repertoire so you can plan specific warm-ups. Because this is hosted in the Vinkius catalog, you connect once to get access to this specialized music tool and thousands of others for all your creative projects. ## Tools ### analyze_transition_smoothness Checks if the musical shift between two songs will be jarring or feel natural to an audience. ### extract_performance_metadata Gathers useful preparation details from your setlist, such as the most common key for vocal warm-ups. ### optimize_set_sequence Rearranges all of your songs into a performance order built around an optimal energy arc. ## Prompt Examples **Prompt:** ``` I have a list of 5 songs. Can you optimize the sequence for a standard energy arc? ``` **Response:** ``` Please provide the JSON array of songs including their BPM, key, duration, and energy level so I can run `optimize_set_sequence` for you. ``` **Prompt:** ``` Are the transitions between these songs smooth: Song A (C Major, 120 BPM) and Song B (F# Major, 140 BPM)? ``` **Response:** ``` No, that transition is likely to be 'Jarring' due to the large distance on the Circle of Fifths and the significant jump in tempo. ``` **Prompt:** ``` What is the most frequent key in my set list? ``` **Response:** ``` The `extract_performance_metadata` tool identifies G Major as your primary warmup key, meaning most of your songs are in that key. ``` ## Capabilities ### Structure Energy Flow It reorders a list of tracks into an ideal performance sequence designed to build tension and hit emotional peaks. ### Check Musical Jumps It evaluates the technical smoothness between songs, flagging potential issues with key or tempo shifts that might sound awkward live. ### Identify Prep Data It pulls out useful performance metadata from your existing setlist, like primary warm-up keys and strategic break points. ## Use Cases ### Structuring the climactic encore A band manager needs to finish a high-energy show with maximum impact. They feed their top 10 songs into the MCP and use `optimize_set_sequence` to ensure the final three tracks build to an undeniable, powerful peak. ### Fixing a tonally awkward transition A musician knows two songs work well but suspects the shift between them is too sudden. They run `analyze_transition_smoothness` on the pair and get immediate confirmation that the key distance needs to be bridged. ### Prepping for a new tour's vocal demands A singer-songwriter collects all their potential material. They run `extract_performance_metadata` across the whole collection and discover that G Major is the dominant key, allowing them to focus their warm-ups correctly. ### Balancing a sprawling 90-minute set The band needs balance. They submit all material to `optimize_set_sequence` and receive a structured arc that balances high-energy numbers with necessary, moodier mid-tempo breaks. ## Benefits - The `optimize_set_sequence` tool reorders your songs automatically, ensuring the setlist builds proper emotional tension instead of just listing tracks. - Avoid awkward stops or sudden shifts. Use `analyze_transition_smoothness` to predict if a tempo jump between two specific songs will sound jarring live. - Plan your vocals smarter. The MCP uses `extract_performance_metadata` to pinpoint the most frequent key in your list, helping you plan targeted warm-ups. - Stop guessing about flow. By analyzing transitions, you gain concrete data on musical compatibility that goes beyond simple genre matching. - Gain a clear view of your performance structure. You get an engineered setlist ready for any venue or audience type. ## How It Works The bottom line is that you get an expert second opinion on your setlist’s architecture, turning raw tracks into a cohesive show plan. 1. Input your song list data, making sure to include key information like BPM, tempo changes, and designated energy levels. 2. Tell the MCP what kind of performance arc you are aiming for (e.g., 'high-energy finale' or 'moody opener'). 3. The system processes the data, returning a reordered sequence with detailed feedback on musical compatibility and performance structure. ## Frequently Asked Questions **How does Set-List Planner optimize_set_sequence?** The MCP analyzes your entire song library to reorder tracks, ensuring a natural energy curve. It balances high and low intensity songs across the set for maximum impact. **Can I use analyze_transition_smoothness for non-musical shifts?** No. This MCP is specialized in music theory. `analyze_transition_smoothness` focuses purely on tempo, key, and scale compatibility between songs. **What kind of data does extract_performance_metadata pull out?** `extract_performance_metadata` pulls preparation details like the most frequent key in your setlist. This helps you focus your vocal warm-up routine effectively. **Does Set-List Planner work with different genres of music?** Yes, as long as you provide the technical metadata (BPM, Key, etc.), this MCP structures setlists regardless of genre. It focuses on musical physics, not style. **Do I need to manually adjust the data before using optimize_set_sequence?** It's best practice to ensure your songs have accurate metadata (BPM, Key, Energy Level) so that `optimize_set_sequence` can build the most precise arc.