Qualify leads with CRM evidence, scoring, knowledge access, and decision gating.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "BRAINS MCP Server" yet — see the docs or source repo.
Use CRM records and knowledge base information to qualify this sales lead, gather evidence, assign a score, and state whether it passes the decision gate.
Returns a lead score, supporting evidence summary, and a clear pass/fail decision.
Run lead qualification for the current user role, using only CRM and knowledge base information accessible to that role, and explain the scoring basis.
Outputs evidence, scoring, and decision reasoning limited to the user's authorized access.
Based on collected customer evidence and scoring rules, produce a deterministic lead approval decision and list the key conditions that triggered it.
Provides an auditable result with score, key evidence, and explicit decision-gating conditions.
Marketing teams can use it to gather evidence from CRM and knowledge bases, then qualify and score potential leads. This helps prioritize follow-up with greater consistency.
When different roles have different access to customer data, it can perform lead qualification within role-based boundaries. This supports review while controlling information exposure.
When teams need fixed rules to decide whether a lead moves forward, it can provide deterministic decision gating. This helps reduce subjective variation and preserve the rationale.
It is an MCP tool for lead qualification. Based on the description, it gathers evidence from CRM, performs scoring, and uses knowledge-base context plus deterministic decision gating to produce results.
Yes. The description explicitly mentions role-based access, indicating it supports role-based control over information access.
The provided material does not include installation steps, runtime requirements, or key requirements. For specific prerequisites, see the source repository.
Enrich prospects, scrape LinkedIn, and sync CRM records with natural language.
Read-only checks for deployment, code integrity, schemas, and docs.
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Break down QA tasks into steps with confidence-scored tool recommendations.