Diego Costa Tech Lead Enrichme
B2B Lead Enrichment MCP API An MCP-native API engineered for AI agents to instantly enrich B2B company profiles with structured firmographic, technographic, an…
What it does
The specific capability behind this listing, and where to get it.
B2B Lead Enrichment MCP API An MCP-native API engineered for AI agents to instantly enrich B2B company profiles with structured firmographic, technographic, and real-time intent data. Unlike legacy REST APIs that require complex middleware to work with LLMs, this server speaks the Model Context Protocol natively. It allows agents like Claude Desktop, Cursor, and custom agent swarms to discover and call enrichment tools reliably, without hallucinating parameters. Core Features Comprehensive Data Layers: Extract company size, verified industry, estimated revenue, complete software stack, and actionable buying intent signals. Built for Agents: Every input parameter is strictly typed and documented with Zod annotations, giving LLMs the exact semantic context they need. Risk-Free Metered Billing: You are only billed for successful, high-confidence enrichments (Confidence Score > 0.6). Failed queries or low-quality data cost $0. The enrich_lead Tool The primary tool exposed by this serv
Official Diego Costa Tech Lead Enrichme links
Pricing & plans
Observed public pricing for Diego Costa Tech Lead Enrichme, benchmarked against comparable providers. Plans, tiers, history and scenario below.
$0.05 /call
This plan sits close to the market.
No monthly-comparable cohort to benchmark this plan against yet.
Why Agentery reaches that view
price_benchmarkNot monthly-comparable.
get_agent_profile · plan historyper call observed 2026-07-22.
pricing recommendationPercentile unavailable for this basis.
confidenceSource page rechecked daily.
Test a different price for this plan.
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Is Diego Costa Tech Lead Enrichme good value?
How its price compares with genuinely comparable providers.
Not enough evidence yet to call it good — or poor — value.
Too few comparable providers at the same buyer tier and billing unit to benchmark this price honestly.
Check capability before deciding
Compare capability, compatibility and operational cost against the few observed peers — Agentery keeps the price status explicit and never invents a verdict.
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "diego_costa_tech_lead_enrichme",
"name": "Diego Costa Tech Lead Enrichme",
"url": "https://lead-enrichment-mcp.agent-infra.workers.dev/",
"logo": null,
"niche": null,
"category": null,
"short_summary": "B2B Lead Enrichment MCP API\nAn MCP-native API engineered for AI agents to instantly enrich B2B company profiles with structured firmographic, technographic, an…",
"task_performed": "B2B Lead Enrichment MCP API\nAn MCP-native API engineered for AI agents to instantly enrich B2B company profiles with structured firmographic, technographic, and real-time intent data.\n\nUnlike legacy REST APIs that require complex middleware to work with LLMs, this server speaks the Model Context Protocol natively. It allows agents like Claude Desktop, Cursor, and custom agent swarms to discover and call enrichment tools reliably, without hallucinating parameters.\n\nCore Features\nComprehensive Data Layers: Extract company size, verified industry, estimated revenue, complete software stack, and actionable buying intent signals.\n\nBuilt for Agents: Every input parameter is strictly typed and documented with Zod annotations, giving LLMs the exact semantic context they need.\n\nRisk-Free Metered Billing: You are only billed for successful, high-confidence enrichments (Confidence Score > 0.6). Failed queries or low-quality data cost $0.\n\nThe enrich_lead Tool\nThe primary tool exposed by this serv",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [
"MCP"
],
"protocols_or_interfaces": [
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],
"industry_fit": [
"developer tools"
],
"autonomy_level": "infrastructure",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
"observed": true,
"billing": "freemium",
"currency": "USD",
"lowest_monthly_usd": 49,
"monthly_usd": 49,
"headline": "Free tier, then from $49/mo",
"summary": "Free tier, then from $49/mo. Lead Enrichment MCP offers a free tier with 100 enrichments per month, a $49/month Pro plan with usage-based overage charges, and custom Enterprise pricing.",
"confidence": "medium",
"source_url": "https://lead-enrichment-mcp.agent-infra.workers.dev/",
"checked_at": "2026-07-28T04:45:17.462Z",
"amount": 49,
"display": "From $49/mo",
"plans": [
{
"name": "Free",
"price": "$0",
"period": "month",
"persona": "free",
"highlights": [
"100 enrichments/month",
"Firmographic, technographic, and intent data",
"Structured JSON output"
],
"price_annual": null
},
{
"name": "Pro",
"price": "$49/mo",
"period": "month",
"persona": "pro",
"highlights": [
"First 100 enrichments/month included",
"$0.05 per successful overage enrichment",
"Billed only when confidence exceeds 0.6",
"Instant API key after checkout"
],
"price_annual": null
},
{
"name": "Enterprise",
"price": "Custom",
"period": null,
"persona": "enterprise",
"highlights": [
"Unlimited or negotiated volume",
"Dedicated support and SLA options",
"Custom integrations and procurement support"
],
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}
],
"source": "render+llm"
},
"trust_or_rating_signal": [],
"evidence_quality": "medium",
"entity_type": "infrastructure",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://lead-enrichment-mcp.agent-infra.workers.dev/"
],
"last_checked": "2026-07-19",
"how_to_connect": {
"website": "https://lead-enrichment-mcp.agent-infra.workers.dev/",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": [
"MCP"
],
"note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 372,
"uptime_7d": 1,
"checked_at": "2026-07-28T02:33:06.991Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}