# Voice Leading Checker MCP MCP > Voice Leading Checker analyzes musical harmony by tracking how individual notes move between different chords. It evaluates four voices—Bass, Tenor, Alto, and Soprano—to flag errors like parallel fifths or voice crossing according to classical rules. This tool helps composers instantly verify complex harmonic transitions, giving quality scores and suggested fixes for smooth, correct music. ## Overview - **Category:** analysis - **Price:** Free - **Tags:** harmony, voice-leading, musicology, satb, composition, musical-analysis ## Description You're building a piece of music, but the harmony feels off. You can't quite pinpoint why it sounds dissonant, even if the chords themselves are right. This MCP examines the movement of every note across four distinct melodic lines (SATB). It checks for harmonic mistakes that human ears might miss or take forever to verify—things like parallel fifths, voice crossings, and incorrect structural flow. Instead of manually poring over sheet music and cross-referencing theory books, you send your voicings to the system. The service returns specific violation details, a quality score for the transition, and concrete suggestions on how to fix it. Because this kind of detailed analysis requires absolute trust in the data, every tool call is recorded in a cryptographically signed audit trail. That means you always know exactly what the AI agent checked and why. You connect once from your preferred client—Claude, Cursor, Windsurf, or any MCP-compatible client—and suddenly complex composition rules are actionable. ## Tools ### analyze_voice_conduction Checks the harmonic movement between two specific chord voicings. ### check_voice_hierarchy Confirms that all four voices are correctly ordered in ascending pitch from bass to soprano. ### evaluate_smoothness Generates a quality grade for an entire musical transition based on its overall flow and error count. ## Prompt Examples **Prompt:** ``` Check if this transition is harmonically correct: Initial {bass: 36, tenor: 48, alto: 55, soprano: 67} to Target {bass: 39, tenor: 51, alto: 58, soprano: 70}. ``` **Response:** ``` The `analyze_voice_conduction` tool has analyzed the transition. No parallel fifths or octaves were detected, and the movement is smooth. ``` **Prompt:** ``` Evaluate the smoothness of a transition with 2 violations and a leap magnitude sum of 12. ``` **Response:** ``` Using `evaluate_smoothness`, the quality grade is determined based on the error count and leap magnitude provided. ``` **Prompt:** ``` Is this voicing valid: Bass 40, Tenor 38, Alto 50, Soprano 60? ``` **Response:** ``` The `check_voice_hierarchy` tool indicates this is invalid because the Tenor pitch (38) is lower than the Bass pitch (40), violating the required ascending order. ``` ## Capabilities ### Conduction Analysis It analyzes how the notes move when transitioning between two different chord voicings. ### Structural Validation It validates that the four voices are presented in the required ascending order (Bass to Soprano). ### Smoothness Evaluation It grades a musical transition based on how smooth and acoustically pleasing the overall movement is. ## Use Cases ### A composer needs to check a complex jazz harmony. A user inputs a transition from a dense, initial voicing to a simpler target voicing. The agent uses `analyze_voice_conduction` and reports that while the chords are valid, the movement creates excessive melodic leaps and parallel fifths, requiring specific note adjustments in the Tenor and Alto lines. ### An educator is grading student scores. The agent runs `check_voice_hierarchy` on several submitted voicings. It immediately flags multiple instances where a voice (like the Tenor) dips below the Bass line, proving structural failure and allowing the teacher to grade accurately without manual checking. ### An arranger needs to make a passage sound 'better'. The user runs `evaluate_smoothness` on a section that sounds choppy. The tool returns a low quality score, pointing out the exact moments of high error count and suggesting specific note shifts needed to achieve a smoother acoustic polish. ### A film scoring team needs rapid compliance checks. The agent takes several candidate transitions from different sections of the score. It runs `analyze_voice_conduction` repeatedly, providing a master list of all harmonic violations across 20 minutes of music in minutes. ## Benefits - Pinpoint exact errors: Use `analyze_voice_conduction` to detect specific issues, like forbidden parallel fifths or octaves between chord changes. You don't just get a 'fail'; you get the rule broken and where. - Verify structural flow: Run `check_voice_hierarchy` first. This ensures your foundational voices are always in proper ascending order, fixing basic arrangements that would otherwise sound amateur. - Get a quality grade instantly: Instead of subjective listening tests, `evaluate_smoothness` gives you an objective score based on error count and leap magnitude, helping you gauge the overall polish of the transition. - Build complex routines: Chain this MCP with other tools in the Vinkius catalog to build automated checks that validate entire musical movements across multiple platforms. - Trust the results: Every analysis is captured in a tamper-proof audit trail. You always know exactly what data was used and how the AI arrived at its score. ## How It Works The bottom line is you get an immediate, expert critique of your composition's harmony, pinpointing exactly where and why the music fails its classical rules. 1. You feed the MCP two sets of chord voicings, specifying which notes are in the Bass, Tenor, Alto, and Soprano registers. 2. The system runs three checks: first for structural hierarchy, then for conduction between the chords, and finally grades the overall smoothness score. 3. You receive a detailed report listing all detected harmonic errors (like parallel fifths) along with suggestions to correct them. ## Frequently Asked Questions **How does the analyze_voice_conduction tool work?** It compares two specific chord voicings, determining how the notes move from one set of chords to the next. It detects harmonic violations like parallel fifths or octaves that ruin smooth musical transitions. **Do I need to use check_voice_hierarchy first?** Yes, it’s best practice. Running `check_voice_hierarchy` confirms the foundational structure—that the voices are in proper ascending order (B-T-A-S). This step prevents misleading analysis of movement if the basic structure is already flawed. **What does evaluate_smoothness actually measure?** `evaluate_smoothness` doesn't just count errors; it generates a composite quality grade. This score considers both the number of violations and the magnitude of melodic leaps, giving you a holistic view of the transition’s polish. **Can I use this MCP with other music tools?** Absolutely. You can chain it with other specialized MCPs in the Vinkius catalog to build full automated workflows that test harmony, structure, and flow across multiple musical parameters at once. **What input format does the analyze_voice_conduction tool require for pitches?** You must provide pitches using their numerical MIDI values. The tool requires four specific inputs: Bass, Tenor, Alto, and Soprano. This ensures precise analysis of the harmonic movement. **If my voicing is invalid, how does check_voice_hierarchy report the error?** The tool immediately rejects the data and specifies exactly which pitch violates the ascending order rule. For instance, it will tell you if the Tenor is lower than the Bass. **Are there rate limits when using evaluate_smoothness for large musical passages?** No. Vinkius manages all background processing load on this MCP. You pay per call, and we handle the infrastructure capacity so you don't hit usage caps. **Does the engine detect errors other than parallel fifths or octaves?** Yes. In addition to those classic rules, it flags voice crossing instances and assesses excessively large melodic leaps. The resulting quality score helps gauge overall harmonic tension.