Lead Scoring Calculator

Lead Scoring Calculator MCP Connector for Claude

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Calculate a lead's conversion readiness score instantly using configurable firmographic and behavioral data points.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner

**How to Assess Lead Value in Minutes.**Finding high-potential leads is difficult. Traditional methods rely on guesswork or simple demographic matching, leading teams to waste time nurturing cold contacts. The core problem is accurately quantifying a lead's readiness for sales handoff.The Solution: Weighted Predictive Scoring. This calculator provides an objective score (0-100) based on measurable data. It operates in three steps:1. Gather Profile Data: We first use query_lead_profile_data to collect foundational attributes like company size, industry sector, and job title.2. Retrieve Weights: Next, we call query_scoring_configuration to fetch the latest scoring weights and qualification thresholds (e.g., what constitutes an MQL vs. SQL).3. Calculate Score: Finally, calculate_converted_score executes the weighted algorithm using all gathered data and configuration parameters, returning a composite score, classification status, and estimated conversion probability.Key Advantage: This system moves beyond simple lead counting. It provides actionable intelligence--a definitive status (Cold, Warm, Hot, MQL, SQL)--allowing sales teams to prioritize outreach based on calculated value, maximizing efficiency for the entire pipeline.

lead-scoringmqlsqlfirmographicsbehavioral-dataconversion-rate

3 tools expose this connector's capabilities to your AI agent.

calculate_converted_score

Returns total score, qualification status (Cold/Warm/Hot/MQL/SQL), and estimated conversion probability. Calculate composite lead score with qualification status and conversion probability

query_lead_profile_data

Optionally specify a scoring version ID. Retrieve raw lead profile data for scoring

query_scoring_configuration

Retrieve current scoring configuration weights and thresholds

See how to talk to your AI agent using Lead Scoring Calculator.

Run a full scoring check for lead ID 'L12345' targeting the USA market. I need to know if they are MQL or SQL.

Calling `query_lead_profile_data` for L12345... Calling `query_scoring_configuration` for weights... Final score calculated via `calculate_converted_score`: Total Score 135/100. Status: SQL (Sales Qualified Lead). Conversion Probability Estimate: 85%-90% (High Confidence).

What is the current weight assigned to 'Director' job titles and what are the minimum scores for MQL in Europe?

The scoring configuration tool provides this data. The `query_scoring_configuration` call reveals that 'Director' titles currently carry a weight of 30 points, and the minimum threshold for MQL in Europe is set at 80.

I have gathered all data for a new lead. Calculate the score.

The scoring process is complete. The final calculated score is [TOTAL_SCORE]/100, classifying the lead as a [STATUS]. This indicates a strong potential for conversion, with an estimated probability range of [PROBABILITY]% to [HIGH_END]%.

The scoring model is comprehensive. It combines static **Firmographic Signals** (like company size and industry sector) retrieved via `query_lead_profile_data` with dynamic **Behavioral Signals** (such as page visits or emails opened). The final score weights these signals to give a true picture of intent.

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