# Concurso Score Calculator MCP > Concurso Score Calculator calculates complex final scores for large-scale exams, verifying minimum stage requirements and predicting a candidate's precise rank against available job openings. ## Overview - **Category:** productivity - **Price:** Free - **Tags:** scoring, ranking, exams, automation, civil-service ## Description Managing exam results is complicated. You can’t just add up the points; you need to account for differing weights assigned to written vs. oral stages, plus mandatory passing grades for every single phase. This MCP handles that complexity automatically. It takes raw performance data and runs it through a rigorous scoring process: first, determining if candidates even met minimum required thresholds. Then, it calculates the weighted total score based on predefined importance levels. If scores are identical, specialized logic resolves any ties using a priority hierarchy. Finally, you get an estimate of where that candidate stands relative to open vacancies. Vinkius makes this entire suite of scoring tools available through one connection from your agent. ## Tools ### predict_ranking_position Estimates a candidate's standing in the total pool compared to how many jobs are actually open. ### calculate_weighted_score Calculates a candidate's final score based on performance across different stages and their assigned importance weights. ### resolve_tiebreaker Applies defined rules to select a single winner when multiple candidates have the exact same total weighted score. ### verify_stage_thresholds Checks if a candidate's performance met the minimum required pass grades for every exam stage they took. ## Prompt Examples **Prompt:** ``` Calculate the total score for a candidate with 80 in Written (60%) and 90 in Oral (40%). ``` **Response:** ``` The `calculate_weighted_score` tool would return a total score of 84.0. ``` **Prompt:** ``` Check if a candidate is qualified with scores: Written: 70, Oral: 50, where minimums are Written: 60, Oral: 60. ``` **Response:** ``` The `verify_stage_thresholds` tool would identify 'Oral' as a failed stage and return isQualified: false. ``` **Prompt:** ``` Predict the rank of a candidate with score 85 among competitors [90, 85, 80, 75] for 2 vacancies. ``` **Response:** ``` The `predict_ranking_position` tool would return an estimated rank of 2 and indicate the candidate is within the vacancy limit. ``` ## Capabilities ### Determine weighted scores The MCP calculates a final total score based on performance in different exam stages and their assigned importance weights. ### Check minimum requirements It verifies if each candidate achieved the necessary passing grade for every mandatory stage of the competition. ### Resolve score ties The system uses a defined priority structure to determine a winner when two or more candidates share the same final weighted score. ### Estimate rank position You get an estimated ranking for any candidate relative to the total pool of applicants and available job slots. ## Use Cases ### Handling Failed Prerequisites A coordinator has a roster of 500 candidates with raw scores. Before calculating anything else, they need to know who failed the minimum written exam score (60/100). They use `verify_stage_thresholds`, and the MCP immediately returns a filtered list of only those eligible for further scoring. ### Finalizing Top Candidates The final 5 candidates all scored 89.2 points, but there are only three vacancies. The coordinator uses `resolve_tiebreaker` to apply the secondary criteria (e.g., highest oral score) and definitively select the top three. ### Assessing Overall Field Performance A manager needs to know if a candidate with a score of 85 is competitive when there are 12 vacancies, but their peers scored between 90 and 75. Using `predict_ranking_position` gives them the precise rank (e.g., 'Rank 4 of 12'). ### Calculating Multi-Stage Scores A candidate scores 80 in Written (60% weight) and 95 in Interview (40% weight). Instead of manual math, the team uses `calculate_weighted_score` to get a clean total score of 89. ## Benefits - Stop manual calculations. Use `calculate_weighted_score` to get a definitive total score instantly, eliminating the risk of human arithmetic errors across multiple stages. - Filter out invalid candidates immediately. `verify_stage_thresholds` checks minimum pass requirements for every stage, ensuring only qualified applicants proceed to ranking. - Keep your top talent organized. If scores are tied, `resolve_tiebreaker` applies structured logic to pick the correct winner without debate or extra manual steps. - Get a realistic picture of outcomes. Instead of just a score, `predict_ranking_position` tells you if a candidate's standing puts them within the available job vacancies. - Process large groups faster. The MCP handles the entire scoring pipeline—weighting, threshold checks, and ranking—in one automated sequence. ## How It Works The bottom line is you get an accurate, auditable ranking list that accounts for weights, thresholds, and ties all in one run. 1. First, you provide the raw scores for every stage (written, oral, etc.) and define the percentage weights for those stages. 2. Next, the MCP checks these inputs against minimum required thresholds. It filters out anyone who failed to meet a specific stage's passing grade. 3. Finally, it uses the remaining valid data to calculate the final weighted score and predicts the candidate's rank relative to vacancies. ## Frequently Asked Questions **How does calculate_weighted_score handle different exam sections?** It calculates the total score by multiplying each section's raw performance by its specific weight (e.g., 60% or 40%) and summing those results for a final number. **What if a candidate fails a minimum threshold using verify_stage_thresholds?** The MCP will identify the failed stage, returning 'isQualified: false' for that person. This prevents their score from being used in any final calculations or rankings. **Does resolve_tiebreaker use random selection if scores are equal?** No. It uses a structured priority hierarchy you define, ensuring the winner is chosen based on documented rules rather than chance. **Can I find out my estimated rank using predict_ranking_position?** Yes. You give it your score and the pool of competitors along with vacancy counts; it returns an estimate of where you stand in that group. **What data structure does calculate_weighted_score require for accurate inputs?** It requires a structured set of scores paired with their respective weights. You must provide all stage weights so the tool can ensure they sum to 1.0 before calculating any total score. **If I use verify_stage_thresholds, what happens when required minimum data is missing?** The process fails and reports which threshold was not provided in the input parameters. You must include every minimum requirement defined by the exam body for the tool to run correctly. **For a very large group of candidates, how does predict_ranking_position handle processing load?** The MCP handles ranking calculations in efficient batches and delivers an estimate quickly. It scales well with thousands of entries, though extremely massive datasets might require dividing the input into smaller chunks. **When using resolve_tiebreaker, how is the final winner decided based on priority?** The tiebreaker evaluates criteria in a sequence you specify in the tool's parameters. It checks these rules one by one until it finds a differentiating factor, then declares that candidate as the ultimate winner. **How does the weighted score calculation work?** The `calculate_weighted_score` tool multiplies each stage's achieved score by its assigned weight. The sum of all weights must equal exactly 1.0 for a valid calculation. **What happens if a candidate fails a minimum threshold?** Using `verify_stage_thresholds`, the system checks every stage. If any score is below the required minimum, the candidate is marked as disqualified. **How are ties resolved between candidates?** The `resolve_tiebreaker` tool uses a pre-defined hierarchy of stages. It compares scores stage-by-stage, starting with the most important stage, until a difference is found.