StratoForce AI — MCP Server

MCP serverProductivity

Once this app is added, your AI can answer questions about your Salesforce pipeline, deals, coaching, and competitors. It provides 15 AI revenue intelligence tools built for Salesforce. You get sales answers in a plain conversation instead of searching Salesforce yourself.

Available today. Use it from your connected AI after setup.

Add the app, then ask your AI a question about your pipeline or a specific deal to see it in action.

Then ask your AI: use StratoForce AI — MCP Server

What your AI can do with it

  • Review your Salesforce sales pipeline
  • Look up details on individual deals
  • Surface coaching insights from your Salesforce data
  • Find competitor information stored in Salesforce

From the project's README

As published by stratoforce-ai-llc/stratoforce-mcp-server in README.md.

Revenue intelligence from your Salesforce pipeline, accessible to any AI assistant.

What It Does

Connects your Salesforce revenue data to any MCP-compatible AI client — Claude Desktop, VS Code, Cursor, Windsurf, and more. Ask natural-language questions about your pipeline and get real answers from real data.

Capabilities

Resources (read-only data)

ResourceURIDescription
Pipeline Summarystratoforce://pipeline/summaryOpen deals by stage with totals
Top Dealsstratoforce://pipeline/top-dealsTop 15 opportunities by value
Active Alertsstratoforce://alerts/activeRevenue intelligence alerts (last 7 days)

Tools (LLM-invokable functions)

ToolDescription
get_pipeline_healthComprehensive pipeline health: stages, velocity, win rate, stale deals
get_deal_detailsDeep dive on any opportunity: contacts, conversations, scores
generate_briefingAI pre-call briefing: stakeholders, competitive intel, talking points
scan_risksPipeline risk scan: stale deals, past-due close dates, dark champions
search_dealsSearch deals by name, account, stage, or owner

Prompts (pre-built templates)

PromptDescription
pipeline_reviewWeekly pipeline review for sales meetings
deal_coachingDeal-specific coaching with MEDDIC analysis
forecast_prepForecast call preparation briefing

Setup

Prerequisites

  • Node.js 20+
  • Salesforce CLI (sf) with an authenticated org
  • StratoForce AI managed package installed in your Salesforce org

Install

cd stratoforce-mcp-server
npm install

Configure Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "stratoforce": {
      "command": "node",
      "args": ["/path/to/stratoforce-mcp-server/index.js"],
      "env": {
        "SF_TARGET_ORG": "stratoforce-dev"
      }
    }
  }
}

Test

echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}' | node index.js

Example Conversations

"How's my pipeline looking?" → Uses get_pipeline_health → Returns stage breakdown, win rate, stale deals, forecast

"Generate a briefing for the Acme deal" → Uses search_deals → finds Acme → Uses generate_briefing → Full pre-call prep

"What deals are at risk?" → Uses scan_risks → Returns stale deals, past-due close dates, score drops

"Run the pipeline_review prompt" → Executes full pipeline review combining all tools → Executive summary

Architecture

AI Client (Claude/VS Code/Cursor)
    ↕ MCP Protocol (JSON-RPC over stdio)
StratoForce MCP Server (Node.js)
    ↕ Salesforce REST API + Apex REST
StratoForce Managed Package (data layer)

License

MIT — StratoForce AI, LLC

Signals

Last commit
May 2026

ahel review

  • S4low
    published under tgomolski's namespace; repository belongs to stratoforce-ai-llc

Automated review, not a security audit. Ruleset v1.

Advanced
Delivery
revenue-intelligence MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
Catalog kind
mcp-server
Gateway key
io-github-tgomolski-lgtm-revenue-intelligence
Source
github.com/stratoforce-ai-llc/stratoforce-mcp-server
Hosted endpoint
https://stratoforce-mcp.stratoforce.workers.dev/mcp