Attio MCP Server

This is a Model Context Protocol (MCP) server that provides comprehensive integration with Attio CRM. It enables AI assistants to interact with Attio data through a variety of tools for managing records, objects, lists, tasks, and more, with specialized features for sales pipeline optimization, revenue operations, and customer success.

Standalone npx package for use with Claude Desktop and other MCP clients

Developed by SPAIK (www.spaik.io)

Features

Core CRM Features

• Records Management: Create, update, search, and retrieve records across all Attio objects
• Object & Schema Operations: Manage custom objects and their attributes
• Lists Management: Create and manage lists for organizing records
• Task Management: Create, update, and track tasks linked to records
• Bulk Operations: Import multiple records at once
• Notes & Comments: Add notes to records
• Webhooks: Set up real-time event monitoring
• Resources: Access workspace configuration and available objects

🚀 Sales Pipeline Optimization Features (NEW)

Lead Scoring & Qualification

• Automated Lead Scoring: Calculate lead scores based on customizable criteria (company size, engagement, budget, timeline, authority)
• Activity Tracking: Track and score lead activities (email opens, website visits, content downloads, meetings)
• Lead Qualification: Qualify leads using BANT, MEDDIC, or CHAMP frameworks with automated recommendations

Pipeline Analytics

• Velocity Analysis: Analyze time spent in each stage, identify bottlenecks, and track conversion rates
• Stalled Deal Detection: Automatically identify deals that need attention with risk levels and suggested actions
• Pipeline Health Metrics: Monitor win rates, average deal sizes, and sales cycle lengths

Sales Automation

• Follow-Up Sequences: Create automated nurture, demo follow-up, and proposal sequences
• Task Templates: Generate stage-specific task lists adjusted for deal value
• Smart Reminders: AI-powered reminders based on deal characteristics, stage, and activity

Advanced Forecasting

• AI-Powered Forecasts: Generate revenue forecasts with confidence scenarios (committed, best case, worst case)
• Historical Analysis: Use win rate data to improve forecast accuracy
• Period Breakdown: Monthly and quarterly forecast views with deal-level details

Revenue Operations (RevOps) Features

Revenue Analytics & Forecasting

• Pipeline Analytics: Analyze sales velocity, conversion rates, and stage progression
• Revenue Forecasting: Generate multi-scenario forecasts with confidence levels
• Deal Scoring: AI-powered deal prioritization based on value, stage, and engagement

Cross-Functional Alignment

• Marketing Attribution: Track ROI across campaigns, sources, and channels
• Automated Handoffs: Create workflows for seamless team transitions
• Lead Scoring: Score and prioritize leads based on behavior and fit

Performance & Compensation

• Team Performance Tracking: Individual and team metrics with leaderboards
• Commission Calculation: Automated commission calculations with tiers and accelerators
• Activity Analytics: Correlate activities to outcomes

Financial Integration

• Subscription Metrics: Calculate MRR, ARR, churn rate, and customer LTV
• Contract Management: Track contract values and renewal dates
• Revenue Recognition: Monitor deferred revenue and compliance

Data Governance

• Data Quality Audits: Identify duplicates, missing data, and inconsistencies
• Intelligent Merging: Merge duplicate records while preserving all data
• Validation Rules: Enforce data standards and completeness

Customer Success Features (NEW)

• Health Score Tracking: Calculate and monitor customer health scores based on multiple factors
• Churn Risk Detection: Identify at-risk customers with automated alerts
• Customer Metrics: Track usage, engagement, and satisfaction metrics
• Lifetime Value Analysis: Calculate CLV and revenue forecasting
• Success Plans: Create structured onboarding and adoption plans
• Automated Check-ins: Schedule QBRs and regular customer touchpoints
• Success Reporting: Generate comprehensive customer success dashboards

🧠 Revenue Intelligence Platform (NEW)

Transform your Attio CRM into an AI-powered Revenue Intelligence system that helps startup founders increase revenue by 30-40% through predictive insights and automated workflows.

Unified Revenue Score™

• Holistic Scoring: Single metric (0-100) combining lead quality, deal momentum, and customer health
• Trend Analysis: Track score changes over time with historical data
• Automated Updates: Real-time scoring as data changes
• Actionable Insights: Specific recommendations based on score components

Predictive Analytics

• Deal Predictions: AI-powered close probability, expected close date, and risk identification
• Churn Predictions: Identify at-risk customers 60-90 days before churn
• Expansion Identification: Automatically surface upsell/cross-sell opportunities
• Revenue Forecasting: Multi-scenario forecasts with confidence levels

Revenue Automation

• Smart Workflows: Create automated workflows for lead nurture, deal acceleration, and customer success
• Intelligent Task Creation: AI-generated tasks based on deal stage and customer health
• Alert System: Real-time notifications for critical revenue events
• Cross-functional Handoffs: Seamless transitions between teams

Revenue Analytics

• Attribution Analysis: Multi-touch attribution across all channels
• Velocity Optimization: Identify and fix pipeline bottlenecks
• Health Monitoring: Real-time revenue health dashboards
• Natural Language Queries: Ask questions like "Show me deals closing this month worth over 50k"

AI-Powered Insights

• Daily Revenue Briefings: Automated insights on opportunities and risks
• Action Recommendations: Prioritized next best actions for each record
• Pattern Recognition: Identify successful patterns to replicate
• Anomaly Detection: Spot unusual trends before they impact revenue

Prerequisites

• Node.js 18+
• An Attio account with API access
• Attio API key (get one from your Attio settings)

🔒 Security Notice

Important: Never pass your API key as a command-line argument. Always use environment variables to keep your credentials secure.

Quick Start

The fastest way to use this server with Claude Desktop:

# Set your API key as an environment variable (recommended)
export ATTIO_API_KEY="your_api_key"
npx @SPAIK/mcp-server-attio

# Or use a .env file for local development
echo "ATTIO_API_KEY=your_api_key" > .env
npx @SPAIK/mcp-server-attio

Claude Desktop Configuration

Add to your Claude Desktop config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "attio": {
      "command": "npx",
      "args": ["@SPAIK/mcp-server-attio"],
      "env": {
        "ATTIO_API_KEY": "your_api_key_here"
      }
    }
  }
}

Development Setup

1. Clone and Install

git clone <repository-url>
cd mcp-server-attio
npm install

# Copy the example environment file
cp .env.example .env
# Edit .env and add your API key

2. Build the Server

npm run build

3. Test Locally

# Set your API key
export ATTIO_API_KEY="your_api_key"

# Run the server
./dist/index.js

# Run tests
npm test

# Run with inspector
npm run inspect

Integrating with AI Tools

Once published to npm, you can integrate the Attio MCP server with various AI tools that support the Model Context Protocol.

Publishing to npm

# The package is already configured as @SPAIK/mcp-server-attio
npm publish

Integration Examples

Using with MCP Inspector

# Test your server with the official MCP Inspector
npx @modelcontextprotocol/inspector ./dist/index.js YOUR_API_KEY


### Verifying the Integration

After setting up the integration with Claude Desktop, you can verify it's working by:

1. Restart Claude Desktop after updating the configuration
2. Start a new conversation and ask: "What Attio tools are available?"
3. Try a simple command like: "Show me the Attio workspace info"

Common commands to test:

// List all available tools What Attio tools are available?

// Get workspace information Show me the Attio workspace info

// List objects List all Attio objects in my workspace

// Create a test record Create a new person in Attio with name "Test User" and email "[email protected]"

### Troubleshooting

If the integration isn't working:

1. **Check npm package**: Ensure the package is published and accessible
2. **Verify API key**: Ensure your Attio API key is correctly set in the environment variable
3. **Check logs**: Look for error messages in Claude Desktop's logs
4. **Validate API key**: Ensure your Attio API key has the necessary permissions
5. **Test locally**: Run `./dist/index.js YOUR_API_KEY` to test the server directly

## Available Tools

### Records Management

#### `create_record`
Create a new record in any Attio object.

```json
{
  "object_type": "people",
  "attributes": {
    "name": "John Doe",
    "email_addresses": ["[email protected]"],
    "phone_numbers": ["+1234567890"]
  }
}

update_record

Update an existing record.

{
  "object_type": "people",
  "record_id": "rec_123",
  "attributes": {
    "job_title": "Senior Developer"
  }
}

get_record

Retrieve a specific record.

{
  "object_type": "companies",
  "record_id": "rec_456"
}

search_records

Search for records with optional filters.

{
  "object_type": "people",
  "query": "john",
  "filters": [
    {
      "attribute": "job_title",
      "operator": "contains",
      "value": "developer"
    }
  ],
  "limit": 25
}

Object & Schema Management

list_objects

Get all available objects in your workspace.

get_object_schema

Get detailed schema information for an object.

{
  "object_type": "people"
}

create_custom_object

Create a new custom object type.

{
  "api_slug": "projects",
  "singular_noun": "Project",
  "plural_noun": "Projects"
}

add_attribute

Add a new attribute to an object.

{
  "object_type": "projects",
  "api_slug": "budget",
  "title": "Budget",
  "type": "number",
  "is_required": false
}

Lists Management

create_list

Create a new list for organizing records.

{
  "name": "Hot Leads",
  "api_slug": "hot_leads",
  "parent_object": "people"
}

add_to_list

Add a record to a list.

{
  "list_id": "list_123",
  "record_id": "rec_789"
}

get_list_entries

Get all entries in a list.

{
  "list_id": "list_123",
  "limit": 100
}

Task Management

create_task

Create a new task with optional linked records.

{
  "content": "Follow up with customer",
  "linked_records": [
    {
      "target_object": "companies",
      "target_record_id": "rec_123"
    }
  ],
  "deadline": "2024-12-31T23:59:59Z"
}

update_task

Update task details or status.

{
  "task_id": "task_123",
  "is_completed": true
}

list_tasks

List tasks with optional filters.

{
  "is_completed": false,
  "limit": 50
}

complete_task

Mark a task as completed.

{
  "task_id": "task_123"
}

Sales Pipeline Optimization Tools

calculate_lead_score

Calculate a lead score based on multiple criteria with recommendations.

{
  "record_id": "rec_123",
  "object_type": "people",
  "custom_criteria": {
    "companySize": { "weight": 20, "ranges": { "small": 5, "medium": 10, "large": 20 } },
    "engagement": { "weight": 30, "emailOpens": 2, "websiteVisits": 3, "contentDownloads": 5 }
  }
}

Returns a score (0-100), grade (A-D), breakdown by category, and actionable recommendations.

track_lead_activity

Track and log lead activities with automatic engagement scoring.

{
  "record_id": "rec_123",
  "activity_type": "content-download",
  "details": "Downloaded pricing guide",
  "score_impact": 10
}

qualify_lead

Qualify a lead using BANT, MEDDIC, or CHAMP frameworks.

{
  "record_id": "rec_123",
  "framework": "BANT",
  "responses": {
    "budget": 50000,
    "authority": "decision-maker",
    "need": "Critical business requirement",
    "timeline": "this-quarter"
  }
}

analyze_pipeline_velocity

Analyze pipeline velocity metrics and identify bottlenecks.

{
  "deal_object_type": "deals",
  "days_back": 90
}

Returns stage metrics, conversion rates, bottlenecks, and overall pipeline health.

identify_stalled_deals

Find deals that haven't been updated recently and need attention.

{
  "deal_object_type": "deals",
  "threshold_days": 30
}

Returns deals with risk levels, suggested actions, and days since last update.

create_follow_up_sequence

Create an automated follow-up sequence for leads.

{
  "record_id": "rec_123",
  "sequence_type": "nurture"
}

Available sequences: nurture, demo-follow-up, proposal-follow-up, or custom.

generate_task_templates

Generate stage-specific task templates for deals.

{
  "stage": "proposal",
  "deal_value": 100000
}

Returns prioritized task lists adjusted for deal value and stage.

create_smart_reminders

Create intelligent reminders based on deal characteristics.

{
  "deal_id": "deal_123"
}

Automatically creates reminders for at-risk deals, approaching deadlines, and required actions.

generate_sales_forecast

Generate AI-powered sales forecast with multiple scenarios.

{
  "forecast_period": 90
}

Returns committed, best case, worst case, and most likely revenue scenarios.

Utility Tools

bulk_import

Import multiple records at once.

{
  "object_type": "people",
  "records": [
    {
      "name": "Alice Smith",
      "email_addresses": ["[email protected]"]
    },
    {
      "name": "Bob Johnson",
      "email_addresses": ["[email protected]"]
    }
  ]
}

generate_sales_report

Generate a comprehensive sales report with deals, companies, and contact emails.

{
  "days_back": 7,
  "deal_object_type": "deals",
  "include_contacts": true
}

This tool will:

• Fetch all deals created in the specified time period
• Retrieve associated company information for each deal
• Collect all contact emails from those companies
• Calculate summary statistics (total value, stage breakdown)
• Return a formatted report with all contact emails

add_note

Add a note to a record.

{
  "target_object": "companies",
  "target_record_id": "rec_123",
  "content": "Had a great meeting, moving forward with the deal"
}

get_workspace_info

Get information about the current workspace.

Revenue Intelligence Tools

calculate_revenue_score

Calculate unified revenue score across lead, deal, and customer lifecycle.

{
  "record_type": "companies",
  "record_id": "rec_123"
}

Returns a comprehensive score (0-100) with insights and recommendations.

predict_revenue_outcomes

Generate AI predictions for deals and customer churn.

{
  "prediction_type": "deal",  // or "churn"
  "record_id": "deal_456"
}

identify_expansion_opportunities

Find upsell, cross-sell, and renewal opportunities.

{
  "customer_id": "company_789"
}

generate_revenue_insights

Get AI-powered insights across your revenue pipeline.

{
  "insight_types": ["deals", "customers", "pipeline"]
}

monitor_revenue_health

Real-time monitoring with configurable alerts.

{
  "alert_thresholds": {
    "pipeline_coverage": 3,
    "win_rate_min": 20
  }
}

query_revenue_natural

Query revenue data using natural language.

{
  "query": "Show me all deals closing this month worth over 50k"
}

create_webhook

Create a webhook for real-time events.

{
  "target_url": "https://your-app.com/webhook",
  "events": ["record.created", "record.updated"]
}

Revenue Operations (RevOps) Tools

analyze_pipeline

Analyze sales pipeline metrics including velocity, conversion rates, and stage progression.

{
  "deal_object_type": "deals",
  "date_range_days": 90,
  "group_by": "stage"  // Options: "stage", "owner", "source", "product"
}

Returns comprehensive pipeline analysis including:

• Total deals and pipeline value
• Average deal size and days to close
• Win/loss rates
• Stage conversion rates
• Pipeline velocity metrics
• Grouped analysis by selected dimension

forecast_revenue

Generate revenue forecasts based on pipeline data and historical performance.

{
  "deal_object_type": "deals",
  "forecast_months": 3,
  "confidence_levels": true,
  "include_recurring": false
}

Provides three forecast scenarios:

• Conservative: Only high-probability deals (>70%)
• Likely: Probability-weighted forecast
• Optimistic: 90% close rate scenario

score_deals

Score and prioritize deals based on multiple factors.

{
  "deal_object_type": "deals",
  "include_closed": false,
  "scoring_factors": ["value", "stage", "age", "activity", "completeness"]
}

Scores deals on a 0-100 scale considering:

• Deal value (0-30 points)
• Sales stage (0-25 points)
• Deal age (0-20 points)
• Recent activity (0-15 points)
• Data completeness (0-10 points)

calculate_lead_attribution

Calculate marketing attribution and ROI for leads and deals.

{
  "people_object_type": "people",
  "deal_object_type": "deals",
  "attribution_window_days": 90
}

Analyzes attribution by:

• Lead source
• Campaign
• Channel
• Calculates ROI and win rates for each

create_handoff_workflow

Create automated handoff workflows between teams.

{
  "workflow_type": "sales_to_cs",  // Options: "sales_to_cs", "marketing_to_sales", "cs_to_sales", "custom"
  "trigger_conditions": [
    {
      "field": "status",
      "operator": "equals",
      "value": "closed_won"
    }
  ],
  "actions": [
    {
      "type": "create_task",
      "details": {
        "content": "Schedule onboarding call",
        "assignee": "cs_team"
      }
    }
  ],
  "source_object": "deals"
}

calculate_team_performance

Calculate team and individual performance metrics.

{
  "team_member_ids": ["member_123", "member_456"],  // Optional, analyzes all if empty
  "period_days": 30,
  "metrics": ["activity", "pipeline", "conversion", "velocity"]
}

Returns:

• Activity metrics (tasks, deals created/updated)
• Pipeline metrics (total deals, value, stage distribution)
• Conversion metrics (win rate, revenue generated)
• Velocity metrics (average days to close, stalled deals)

calculate_commissions

Calculate sales commissions based on configurable rules.

{
  "commission_rules": {
    "base_rate": 0.1,  // 10% base commission
    "tiers": [
      { "threshold": 50000, "rate": 0.12 },
      { "threshold": 100000, "rate": 0.15 }
    ],
    "accelerators": [
      { "condition": "deal_size > 25000", "multiplier": 1.2 },
      { "condition": "new_logo", "multiplier": 1.5 }
    ]
  },
  "period": {
    "start_date": "2024-01-01",
    "end_date": "2024-01-31"
  }
}

calculate_subscription_metrics

Calculate key subscription metrics including MRR, ARR, churn, and LTV.

{
  "subscription_object_type": "subscriptions",
  "company_object_type": "companies",
  "date_range_months": 12
}

Calculates:

• Monthly Recurring Revenue (MRR)
• Annual Recurring Revenue (ARR)
• Gross and net churn rates
• Customer lifetime value (LTV)
• Average revenue per account (ARPA)
• Monthly cohort analysis

audit_data_quality

Audit data quality across objects and identify issues.

{
  "object_types": ["people", "companies", "deals"],
  "check_types": ["duplicates", "completeness", "consistency", "validation"]
}

Identifies:

• Duplicate records
• Missing required fields
• Incomplete records
• Invalid data formats
• Provides data quality score

merge_duplicate_records

Merge duplicate records intelligently.

{
  "object_type": "people",
  "primary_record_id": "rec_123",
  "duplicate_record_ids": ["rec_456", "rec_789"],
  "merge_strategy": "most_complete"  // Options: "keep_primary", "most_complete", "most_recent"
}

Intelligently merges records by:

• Preserving all data
• Combining arrays (emails, phones)
• Using most complete/recent values
• Creating audit trail
• Adding merge notes

Customer Success Tools

calculate_health_score

Calculate customer health score based on multiple weighted factors.

{
  "company_id": "rec_123",
  "metrics": {
    "usage_score": 85,
    "engagement_score": 70,
    "support_score": 90,
    "payment_score": 100,
    "adoption_score": 60
  },
  "weights": {
    "usage": 0.3,
    "engagement": 0.2,
    "support": 0.2,
    "payment": 0.2,
    "adoption": 0.1
  }
}

This calculates a weighted health score and updates the company record with the score, status (healthy/needs_attention/at_risk), and individual metric scores.

identify_churn_risks

Identify customers at risk of churning based on multiple factors.

{
  "days_inactive": 30,
  "health_score_threshold": 60,
  "include_payment_issues": true,
  "limit": 50
}

Returns a prioritized list of at-risk customers with risk levels (critical/high/medium) and specific risk factors.

track_customer_metrics

Update customer usage and engagement metrics.

{
  "company_id": "rec_123",
  "metrics": {
    "daily_active_users": 45,
    "monthly_active_users": 120,
    "feature_adoption": {
      "dashboard": true,
      "api": true,
      "integrations": false
    },
    "last_login_date": "2024-01-20T10:30:00Z",
    "api_calls_count": 15000,
    "nps_score": 8
  }
}

Updates company metrics and calculates trends like MAU growth and feature adoption rate.

calculate_customer_lifetime_value

Calculate CLV and key revenue metrics.

{
  "company_id": "rec_123",
  "monthly_revenue": 5000,
  "start_date": "2023-01-15",
  "expansion_revenue": 2000,
  "churn_probability": 0.15
}

Calculates expected lifetime, CLV, and updates revenue-related attributes on the company.

create_success_plan

Create structured success plans with milestones and automated tasks.

{
  "company_id": "rec_123",
  "plan_type": "onboarding",
  "milestones": [
    {
      "title": "Initial Setup Complete",
      "description": "All integrations connected and data imported",
      "due_days": 7,
      "success_criteria": "3+ integrations active, 1000+ records imported"
    },
    {
      "title": "First Value Achievement",
      "description": "Customer achieves first measurable business outcome",
      "due_days": 30,
      "success_criteria": "10% efficiency improvement documented"
    }
  ],
  "assigned_to": "member_456"
}

Creates a success plan with a dedicated list and tasks for each milestone.

generate_customer_success_report

Generate comprehensive customer success analytics.

{
  "time_period_days": 30,
  "segment": "at_risk",
  "include_recommendations": true
}

Generates a detailed report with:

• Customer health distribution
• Revenue at risk
• Average health scores
• NPS analysis
• Actionable recommendations

schedule_customer_check_in

Automate customer check-ins and QBRs.

{
  "company_id": "rec_123",
  "check_in_type": "quarterly",
  "topics": [
    "Review business outcomes",
    "Discuss expansion opportunities",
    "Address any blockers",
    "Plan next quarter goals"
  ],
  "start_date": "2024-02-01",
  "assignee_id": "member_456"
}

Creates recurring check-in tasks with preparation notes and topics.

Resources

The server provides read-only resources that can be accessed by AI assistants:

• workspace_info: Current workspace configuration and details
• available_objects: List of all available objects in the workspace

Prompts

The server includes helpful prompts for common workflows:

Sales & CRM Prompts

• import_contacts_csv: Step-by-step guide for importing contacts from CSV
• create_sales_pipeline: Guide for setting up a complete sales pipeline
• task_automation: Instructions for automating task creation
• weekly_sales_report: Guide for generating weekly sales reports with contact emails

Customer Success Prompts

• setup_health_scoring: Complete guide for implementing customer health scoring
• churn_prevention_workflow: Automated workflows for preventing customer churn
• customer_onboarding: Structured onboarding automation setup
• expansion_identification: Systematic approach to finding upsell opportunities

Use Cases

🎯 Sales Pipeline Optimization for Startup Founders

Increasing Conversion Rates

1. Implement Lead Scoring

Calculate lead scores for all contacts created this week

The AI will:

• Score leads based on company size, engagement, budget, timeline, and authority
• Provide A-D grades with specific recommendations
• Suggest routing rules (A grades to senior reps, B grades to standard team, etc.)
• Track conversion rates by score grade to optimize the model

2. Qualify Leads Systematically

Qualify this lead using BANT framework

The AI will:

• Run through Budget, Authority, Need, Timeline questions
• Calculate qualification score
• Provide specific recommendations for moving forward
• Suggest next steps based on qualification results

Reducing Sales Cycle Time

1. Identify and Fix Pipeline Bottlenecks

Analyze our pipeline velocity and show me the bottlenecks

The AI will:

• Calculate average time in each stage
• Identify stages taking 50%+ longer than average
• Show conversion rates between stages
• Provide specific actions to speed up slow stages

2. Automate Follow-Up Sequences

Create a demo follow-up sequence for this contact

The AI will automatically:

• Schedule thank you email (same day)
• Create task for sending demo recording (day 1)
• Schedule feedback call (day 3)
• Set proposal deadline (day 7)
• Create follow-up reminders (day 10)

3. Manage Stalled Deals

Show me all stalled deals that need attention

The AI will:

• Find deals with no activity in 30+ days
• Categorize by risk level (high/medium/low)
• Provide specific re-engagement actions
• Calculate total revenue at risk

Improving Deal Visibility and Forecasting

1. Generate Accurate Forecasts

Generate a sales forecast for the next quarter

The AI provides:

• Committed revenue (>70% probability)
• Best case scenario (all deals close)
• Most likely scenario (probability-weighted)
• Worst case scenario (80% of committed)
• Monthly breakdown with specific deals

2. Create Smart Deal Reminders

Create smart reminders for all my high-value deals

The AI will:

• Analyze each deal's stage, value, and activity
• Create reminders for deals needing attention
• Flag deals past expected close date
• Alert on high-value deals with no recent activity

Weekly Sales Report Generation

The MCP server can generate comprehensive sales reports that include:

• All deals from a specified time period
• Associated company information
• Contact emails for all people linked to those companies
• Summary statistics and stage breakdown

Example usage in Claude Code:

Generate a weekly sales report for the last 7 days including all contact emails

The AI will use the generate_sales_report tool to:

1. Fetch deals from the past week
2. Get company details for each deal
3. Retrieve all contacts with their email addresses
4. Compile a formatted report with totals and email lists

This is perfect for:

• Weekly sales team meetings
• Email campaign targeting
• Pipeline analysis
• Customer outreach planning

Revenue Operations for Startup Founders

Building a Scalable Revenue Engine

Startup founders can use the RevOps tools to build a data-driven revenue engine:

1. Pipeline Velocity Optimization

Analyze our sales pipeline velocity and identify bottlenecks

The AI will use analyze_pipeline to:

• Calculate average time in each stage
• Identify stages with highest drop-off rates
• Compare performance across reps and segments
• Provide actionable recommendations

2. Revenue Forecasting & Planning

Generate a 3-month revenue forecast with different scenarios

The AI will use forecast_revenue to:

• Create conservative, likely, and optimistic scenarios
• Factor in historical win rates by stage
• Account for seasonality
• Help with resource planning and hiring decisions

3. Cross-Functional Alignment

Calculate marketing attribution and ROI for our campaigns

The AI will use calculate_lead_attribution to:

• Track which campaigns drive revenue
• Calculate cost per acquisition by channel
• Identify highest ROI activities
• Optimize marketing spend allocation

4. Team Performance & Compensation

Calculate monthly commissions and performance metrics for the sales team

The AI will use calculate_team_performance and calculate_commissions to:

• Track individual and team performance
• Calculate commissions with tiers and accelerators
• Identify top performers and coaching opportunities
• Ensure fair and motivating compensation

5. Data Quality & Governance

Audit our CRM data quality and merge duplicates

The AI will use audit_data_quality and merge_duplicate_records to:

• Identify duplicate records
• Find missing critical data
• Merge duplicates intelligently
• Maintain clean, reliable data for decision-making

Subscription Business Management

For SaaS and subscription businesses:

Calculate our key subscription metrics including MRR, churn, and LTV

The AI will use calculate_subscription_metrics to:

• Track MRR growth and cohort retention
• Calculate gross and net churn rates
• Determine customer lifetime value
• Identify expansion opportunities
• Monitor unit economics

Automated Handoff Workflows

Create seamless transitions between teams:

Set up an automated handoff from sales to customer success when deals close

The AI will use create_handoff_workflow to:

• Define trigger conditions (e.g., deal closed won)
• Create onboarding tasks automatically
• Assign to appropriate team members
• Ensure no customer falls through the cracks

Customer Health Monitoring

The server provides comprehensive health scoring to prevent churn:

Example usage:

Calculate health scores for all customers and identify those at risk

The AI will:

1. Use calculate_health_score to compute scores based on usage, engagement, support, and payment data
2. Run identify_churn_risks to find at-risk customers
3. Create intervention tasks for critical accounts
4. Generate recommendations for retention

Automated Customer Success Plans

Create structured success plans for different customer lifecycle stages:

Example usage:

Create an onboarding plan for new customer Acme Corp with key milestones

The AI will use create_success_plan to:

1. Set up milestone-based tasks
2. Create a dedicated tracking list
3. Assign tasks to team members
4. Set success criteria for each stage

Revenue Expansion Tracking

Identify and capture growth opportunities within existing customers:

Example usage:

Find customers ready for expansion based on usage and health metrics

The system will:

1. Analyze usage patterns approaching limits
2. Check health scores and engagement levels
3. Calculate potential expansion revenue
4. Create targeted upsell tasks

Proactive Customer Engagement

Schedule automated check-ins based on customer tier and health:

Example usage:

Set up quarterly business reviews for all enterprise customers

This will:

1. Use schedule_customer_check_in to create recurring tasks
2. Include preparation checklists
3. Track outcomes and follow-ups
4. Maintain consistent customer touchpoints

Testing

Test with the MCP Inspector

npx @modelcontextprotocol/inspector http://localhost:3000/mcp

Note: You'll need to configure your API key in the Inspector's connection settings.

Test Scripts

The repository includes test scripts in the scripts/ directory:

# Test Attio MCP server (requires API key)
node scripts/test-attio-server.mjs http://localhost:3000 your_api_key_here

# Test Customer Success features (requires API key)
node scripts/test-customer-success.mjs http://localhost:3000 your_api_key_here

# Test standard HTTP client (for generic MCP testing)
node scripts/test-client.mjs http://localhost:3000

# Test SSE/streaming client
node scripts/test-streamable-http-client.mjs http://localhost:3000

The customer success test script will:

• Track customer metrics (usage, engagement, NPS)
• Calculate health scores
• Identify churn risks
• Create success plans with milestones
• Schedule automated check-ins
• Generate success reports

API Rate Limits

Please be aware of Attio's API rate limits. The server includes error handling for rate limit responses, but it's recommended to implement appropriate throttling in your application.

Error Handling

All tools include comprehensive error handling and will return descriptive error messages if operations fail. Common errors include:

• Missing required fields
• Invalid record/object IDs
• Insufficient permissions
• API rate limits exceeded

Security

• API Key Storage: Your Attio API key is stored in your local MCP client configuration (Claude Code, Cursor, etc.) and is never exposed to the server logs
• Never commit API keys: Ensure your MCP client configuration files containing API keys are not committed to version control
• Local Development: When running locally, the API key is passed securely from the MCP client to the server
• Production Deployment: When deployed, the API key is transmitted securely over HTTPS from your MCP client
• Access Control: Consider implementing additional authentication layers if exposing the MCP server publicly
• Workspace Isolation: Use the optional workspaceId configuration to restrict access to specific Attio workspaces

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

For questions, feedback, or support, please contact us at [email protected].

Maintained by SPAIK (www.spaik.io)

License

MIT License - see LICENSE file for details