The Problem: > Most AI agents today are trapped in chat windows. While models are smart enough to run complex multi-step workflows, giving them production access to business context (CRM, support, billing) usually means managing unsafe local API keys or hacking together fragile point-solution scripts.
What We Built: We built Salestrics to serve as both an all-in-one revenue workspace (CRM, service desk, billing, docs, email) and a production-grade Model Context Protocol (MCP) execution proxy.
How It Works:
Unified Context: Instead of fragmenting data across five SaaS tools, customer records, tickets, and invoices live in a single data layer.
165-Tool MCP Server: You connect your local AI environment (Cursor, Claude Desktop, local LLMs) once via our MCP proxy.
Full-CRUD Execution: Your agent gets zero-config execution access across native apps and third-party tools (Stripe, PostHog, Sentry)—allowing it to do things like resolve support tickets, issue refunds, or update pipeline stages directly from your IDE or chat client.
Human-in-the-Loop Governance: High-impact agent actions (deleting records, mass messaging, issuing payouts) trigger explicit approval gates and immutable audit logs before execution.
Traction & Tech Stack: We launched two months ago and currently power 320+ active organizations. The backend is built with high-throughput node/TypeScript orchestration, connected to a dual-model AI routing engine (Salestrics-AI-v1/v2).
Try It Out: We have a Free Forever tier for solo builders. You can grab your MCP keys and test the proxy immediately without putting down a credit card.
I’d love to hear your thoughts on our MCP architecture, human-in-the-loop security patterns, or what tools/actions you'd want added to the MCP server next!
Show HN: Salestrics – An open MCP server and CRM for AI-native revenue teams
salestrics.com