What is MCP and why does it matter for sales?
Brief explanation of Model Context Protocol — lets AI assistants like Claude call external tools via natural language.
The problem with manual outreach workflows
Developers and technical founders spend hours context-switching between prospecting tools, enrichment tools, and sequencers.
How toflow.ai's MCP server works
- Connect toflow.ai as an MCP server in Claude
- What tools become available (prospect search, enrich, enroll in sequence)
- Code snippet: the MCP config JSON
Step-by-step: From ICP to booked demo in Claude
- Describe your ICP in plain English
- Claude calls toflow.ai to search LinkedIn
- Claude enriches contact data
- Claude enrolls into a sequence
Example prompts that work
Find 25 VP of Sales at B2B SaaS companies in the US
with 20 to 100 employees who have posted on LinkedIn
in the last 30 days. Save them to a list called
"VP Sales US - July 2026".
Enrich all contacts in "VP Sales US - July 2026".
Find verified work emails and LinkedIn profile data.
Flag anyone missing an email.
Create a sequence called "LinkedIn First - Warm".
Step 1: LinkedIn connection request on day 1.
Step 2: LinkedIn message on day 3 if they accept.
Step 3: Email follow-up on day 7 if no reply.
Step 4: Final email on day 14.
Go through my inbox and label every reply as
interested, not interested, or out of office.
Flag the interested ones for me to review.
Why this matters for technical founders
Skip the sales dashboard — run outreach from the same AI assistant you already use.
Built with toflow.ai — AI-native outreach across email, LinkedIn and whatsapp.
Top comments (0)