clay-load-scale
Implement Clay load testing, auto-scaling, and capacity planning strategies. Use when running performance tests, configuring horizontal scaling, or planning capacity for Clay integrations. Trigger with phrases like "clay load test", "clay scale", "clay performance test", "clay capacity", "clay k6", "clay benchmark".
Install
mkdir -p .claude/skills/clay-load-scale && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5498" && unzip -o skill.zip -d .claude/skills/clay-load-scale && rm skill.zipInstalls to .claude/skills/clay-load-scale
About this skill
Clay Load & Scale
Overview
Strategies for processing 10K-100K+ leads through Clay monthly. Clay is a hosted platform -- you can't add servers. Scaling focuses on: table partitioning, webhook management, batch submission pacing, credit budgeting at scale, and multi-table architectures.
Prerequisites
- Clay Growth or Enterprise plan
- Understanding of Clay's credit model (Data Credits + Actions)
- Queue infrastructure for batch processing (Redis, SQS, or BullMQ)
- Monitoring for credit consumption
Instructions
Step 1: Capacity Planning
// src/clay/capacity-planner.ts
interface CapacityPlan {
monthlyLeads: number;
creditsPerLead: number;
totalCreditsNeeded: number;
planRequired: string;
estimatedMonthlyCost: number;
webhooksNeeded: number; // Each webhook has 50K lifetime limit
tablesRecommended: number;
}
function planCapacity(monthlyLeads: number, creditsPerLead = 6): CapacityPlan {
const totalCredits = monthlyLeads * creditsPerLead;
// Determine plan
let plan: string, cost: number;
if (totalCredits <= 2500) {
plan = 'Launch ($185/mo)';
cost = 185;
} else if (totalCredits <= 6000) {
plan = 'Growth ($495/mo)';
cost = 495;
} else {
plan = `Enterprise (custom pricing for ${totalCredits} credits/mo)`;
cost = 495 + Math.ceil((totalCredits - 6000) / 1000) * 50; // Rough estimate
}
// With own API keys: 0 data credits, only actions consumed
console.log(`TIP: With own API keys, you need 0 Data Credits.`);
console.log(` Only ${monthlyLeads} Actions needed (Growth plan includes 40K).`);
return {
monthlyLeads,
creditsPerLead,
totalCreditsNeeded: totalCredits,
planRequired: plan,
estimatedMonthlyCost: cost,
webhooksNeeded: Math.ceil(monthlyLeads / 50_000 * 12), // Annual webhooks needed
tablesRecommended: Math.ceil(monthlyLeads / 10_000), // ~10K rows per table for manageability
};
}
// Example
const plan = planCapacity(50_000);
console.log(plan);
// Monthly leads: 50,000
// Credits needed: 300,000 (or 0 with own API keys)
// Webhooks needed: 12/year
// Tables recommended: 5
Step 2: Implement Batch Queue Architecture
// src/clay/batch-processor.ts
import { Queue, Worker } from 'bullmq';
import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL!);
// Create a queue for Clay webhook submissions
const clayQueue = new Queue('clay-enrichment', { connection: redis });
interface EnrichmentJob {
leads: Record<string, unknown>[];
webhookUrl: string;
batchId: string;
priority: 'high' | 'normal' | 'low';
}
// Submit a batch for processing
async function queueBatch(
leads: Record<string, unknown>[],
webhookUrl: string,
priority: 'high' | 'normal' | 'low' = 'normal',
): Promise<string> {
const batchId = `batch-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
// Split into chunks of 100 for manageable processing
const chunks = [];
for (let i = 0; i < leads.length; i += 100) {
chunks.push(leads.slice(i, i + 100));
}
for (let i = 0; i < chunks.length; i++) {
await clayQueue.add(`${batchId}-chunk-${i}`, {
leads: chunks[i],
webhookUrl,
batchId,
priority,
}, {
priority: priority === 'high' ? 1 : priority === 'normal' ? 5 : 10,
attempts: 3,
backoff: { type: 'exponential', delay: 5000 },
});
}
console.log(`Queued ${leads.length} leads in ${chunks.length} chunks (batch: ${batchId})`);
return batchId;
}
// Worker processes queued batches
const worker = new Worker<EnrichmentJob>('clay-enrichment', async (job) => {
const { leads, webhookUrl } = job.data;
let sent = 0, failed = 0;
for (const lead of leads) {
try {
const res = await fetch(webhookUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(lead),
});
if (res.status === 429) {
const retryAfter = parseInt(res.headers.get('Retry-After') || '60');
console.log(`Rate limited. Waiting ${retryAfter}s...`);
await new Promise(r => setTimeout(r, retryAfter * 1000));
// Retry this lead
const retry = await fetch(webhookUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(lead),
});
if (retry.ok) sent++; else failed++;
} else if (res.ok) {
sent++;
} else {
failed++;
}
} catch {
failed++;
}
// Pace submissions: 200ms between rows
await new Promise(r => setTimeout(r, 200));
}
return { sent, failed, total: leads.length };
}, { connection: redis, concurrency: 1 });
Step 3: Multi-Table Strategy
For large volumes, split data across multiple Clay tables:
# Large-volume table strategy
tables:
outbound-leads-tech:
focus: "Technology companies"
filter: "industry IN ('Software', 'SaaS', 'Technology')"
enrichment: Full waterfall + Claygent
volume: ~5K rows/month
outbound-leads-finance:
focus: "Financial services companies"
filter: "industry IN ('Financial Services', 'Banking', 'Insurance')"
enrichment: Full waterfall (no Claygent — regulated data)
volume: ~3K rows/month
inbound-leads:
focus: "Website form submissions"
source: Webhook from web forms
enrichment: Company lookup + email verification only
volume: ~2K rows/month
auto_delete: true # Stream-through: enrich, push to CRM, delete
event-attendees:
focus: "Conference/webinar registrants"
source: CSV import
enrichment: Full waterfall + AI personalization
volume: ~1K rows/month (batch after events)
Step 4: Webhook Rotation for High Volume
// src/clay/webhook-rotation.ts
class WebhookRotator {
private webhooks: { url: string; count: number; maxCount: number }[];
private currentIndex = 0;
constructor(webhookUrls: string[], maxPerWebhook = 45_000) {
this.webhooks = webhookUrls.map(url => ({
url,
count: 0,
maxCount: maxPerWebhook, // Leave 5K buffer under 50K limit
}));
}
getNextWebhook(): string {
// Find a webhook with remaining capacity
for (let i = 0; i < this.webhooks.length; i++) {
const idx = (this.currentIndex + i) % this.webhooks.length;
if (this.webhooks[idx].count < this.webhooks[idx].maxCount) {
this.currentIndex = idx;
return this.webhooks[idx].url;
}
}
throw new Error('All webhooks exhausted! Create new webhooks in Clay.');
}
recordSubmission() {
this.webhooks[this.currentIndex].count++;
}
getStatus() {
return this.webhooks.map((w, i) => ({
index: i,
remaining: w.maxCount - w.count,
percentUsed: ((w.count / w.maxCount) * 100).toFixed(1),
}));
}
}
// Usage: rotate across multiple webhooks for the same table
const rotator = new WebhookRotator([
process.env.CLAY_WEBHOOK_URL_1!,
process.env.CLAY_WEBHOOK_URL_2!,
process.env.CLAY_WEBHOOK_URL_3!,
]);
Step 5: Auto-Delete for Stream-Through Processing
For high-volume use cases where Clay enriches and pushes data onward, enable auto-delete to keep tables lean:
In Clay UI: Table Settings > Auto-delete
When enabled, Clay enriches incoming webhook data, sends results via HTTP API column to your destination, then deletes the rows. This keeps Clay functioning as a streaming enrichment service rather than a database.
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Processing stuck at 400/hr | Explorer plan throttle | Upgrade to Growth (no throttle) |
| Webhook exhausted (50K) | High volume | Rotate to new webhook, implement rotator |
| Queue backing up | Webhook rate limiting | Reduce concurrency, increase delay |
| Table too large to manage | 10K+ rows | Split into multiple focused tables |
| Credit overrun | Uncontrolled batch size | Add budget check before queueing |
Resources
Next Steps
For reliability patterns, see clay-reliability-patterns.
More by jeremylongshore
View all skills by jeremylongshore →You might also like
flutter-development
aj-geddes
Build beautiful cross-platform mobile apps with Flutter and Dart. Covers widgets, state management with Provider/BLoC, navigation, API integration, and material design.
drawio-diagrams-enhanced
jgtolentino
Create professional draw.io (diagrams.net) diagrams in XML format (.drawio files) with integrated PMP/PMBOK methodologies, extensive visual asset libraries, and industry-standard professional templates. Use this skill when users ask to create flowcharts, swimlane diagrams, cross-functional flowcharts, org charts, network diagrams, UML diagrams, BPMN, project management diagrams (WBS, Gantt, PERT, RACI), risk matrices, stakeholder maps, or any other visual diagram in draw.io format. This skill includes access to custom shape libraries for icons, clipart, and professional symbols.
ui-ux-pro-max
nextlevelbuilder
"UI/UX design intelligence. 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient."
godot
bfollington
This skill should be used when working on Godot Engine projects. It provides specialized knowledge of Godot's file formats (.gd, .tscn, .tres), architecture patterns (component-based, signal-driven, resource-based), common pitfalls, validation tools, code templates, and CLI workflows. The `godot` command is available for running the game, validating scripts, importing resources, and exporting builds. Use this skill for tasks involving Godot game development, debugging scene/resource files, implementing game systems, or creating new Godot components.
nano-banana-pro
garg-aayush
Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports both text-to-image generation and image-to-image editing with configurable resolution (1K default, 2K, or 4K for high resolution). DO NOT read the image file first - use this skill directly with the --input-image parameter.
fastapi-templates
wshobson
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
Related MCP Servers
Browse all serversEnhance software testing with Playwright MCP: Fast, reliable browser automation, an innovative alternative to Selenium s
Automate API testing with Postman collections or OpenAPI specs. Generate test cases in TypeScript, JavaScript, and Pytho
Connect Claude to Apifox for direct API docs access and testing via env-auth and TypeScript/Express integration.
Discover JNews, a lightweight Python FastAPI server using uv for dependencies and GitHub Actions for CI/CD. Ideal for Fa
Break down complex problems with Sequential Thinking, a structured tool and step by step math solver for dynamic, reflec
Build persistent semantic networks for enterprise & engineering data management. Enable data persistence and memory acro
Stay ahead of the MCP ecosystem
Get weekly updates on new skills and servers.