Lead Scoring Ai Mcp
Let your agent score and prioritize inbound leads from CRM exports or form data so you focus follow-up on prospects most likely to convert.
Overview
lead-scoring-ai-mcp is a MCP server for the Grow phase that enables your agent to score and prioritize leads via a PyPI stdio integration.
What is this MCP server?
- lead-scoring-ai-mcp v1.0.4 on PyPI with stdio MCP transport
- Built for agent workflows that classify or rank leads using MEOK AI Labs tooling
- Pairs with spreadsheets, CRM JSON, or inline lead records the agent already holds in context
- Fits post-launch solo founders who cannot run a full RevOps stack but still need prioritization
- Open GitHub project CSOAI-ORG/lead-scoring-ai-mcp for implementation review
- Catalog server version: 1.0.4
- 1 PyPI identifier: lead-scoring-ai-mcp
- Transport: stdio
What problem does it solve?
You have more inbound leads than hours to reply, and no lightweight way for your coding agent to rank who to contact first.
Who is it for?
Indie SaaS builders with MCP setups who manually qualify leads and want AI-assisted ranking inside the editor.
Skip if: Teams needing enterprise CRM-native scoring, audited models, or real-time webhook pipelines without custom glue code.
What do I get? / Deliverables
After setup, your agent can produce scored or tiered lead lists you can export to email sequences, CRM tasks, or personal outreach queues.
- Prioritized lead rankings or labels from agent-invoked scoring calls
- Reusable MCP tool for weekly or batch qualification sessions
- Version 1.0.4 package pin for reproducible local setups
Recommended MCP Servers
Journey fit
Lead scoring belongs in Grow when you already have traffic or signups and need to compound revenue by ranking who deserves personal outreach. Lifecycle is the canonical shelf because scoring drives nurture, sales touch, and activation decisions rather than top-of-funnel SEO or infra monitoring.
How it compares
Agent-callable scoring MCP, not HubSpot-style native scoring rules or a packaged growth skill.
Common Questions / FAQ
Who is lead-scoring-ai-mcp for?
Solo builders and small teams using MCP agents who want to prioritize sales leads without adopting a full RevOps suite.
When should I use lead-scoring-ai-mcp?
Use it in Grow lifecycle work when signups or demos are steady and you need repeatable prioritization before outreach.
How do I add lead-scoring-ai-mcp to my agent?
Install the PyPI package lead-scoring-ai-mcp, configure stdio in your MCP client, and invoke scoring tools with lead records or CSV snippets your agent can read.