Synlake

{ "status": "success", "recommendation": { "provider": "aws", "instance": "t3.medium", "region": "us-east-1", "monthly_cost": 29.95, "execution_kit": { "terraform_hcl": "resource \"aws_instance\"...", "cli_command": "aws ec2 run-instances...", "validation": "passed" } }, "alternatives": 4, "guardrails": "budget_ok | region_ok" }

Live onMCP RegistryLive onSmithery100free API calls / month3cloud providers normalized

curl -X POST https://api.synlake.ai/v1/infrastructure/query \ -H "Content-Type: application/json" \ -d '{"intent":"compute","service":"compute","requirements":{"vcpus_min":2,"memory_gb_min":4},"constraints":{"budget_monthly_max":100,"providers":["aws"]}}'

Cloud infrastructure wasn'tdesigned for agents.

Today's stack assumes a human at a dashboard. Autonomous agents need machine-ready data — normalized, costed, and executable.

AWS, Azure, and GCP each expose different schemas, pricing models, and APIs. Agents waste cycles on adapters.

Cloud documentation is for humans. Without a normalized JSON contract, every integration is bespoke glue code.

Agents can plan but can't safely act. No cost guardrails, no validation — a human stays in the loop.

Normalize, execute, validate, and audit — all from a single endpoint.

Unified JSON schema across AWS, Azure, and GCP. One contract for compute, storage, and databases — always machine-ready, always current.

{ "service": "compute", "provider": "aws", "instance": "t3.medium", "specs": { "vcpus": 2, "memory_gb": 4, "network": "moderate" }, "price_per_hour": 0.0416, "regions": ["us-east-1", "eu-west-1"] }

Terraform HCL, CLI commands, and API calls — generated and validated on demand. Ready to run, no glue code.

# Terraform HCL — auto-generated resource "aws_instance" "synlake_agent" { ami = "ami-0c55b159cbfafe1f0" instance_type = "t3.medium" tags = { Name = "agent-42-compute" } } # CLI command — ready to paste # aws ec2 run-instances \ # --image-id ami-0c55b159cbfafe1f0 \ # --instance-type t3.medium

Budget caps, region policies, and cost simulation enforced before execution. Every query validates constraints automatically — no surprise bills.

{ "validation": "passed", "checks": { "budget": "$29.95 < $100 limit ✔", "region": "us-east-1 allowed ✔", "security": "no public access ✔", "encryption": "EBS encrypted ✔" }, "spending_cap": { "monthly_limit": 100, "used": 29.95, "remaining": 70.05 } }

Every query logged with request, response, cost, and timestamp. Complete accountability for compliance and cost tracking.

{ "log_id": "req_8f2a4b6c", "timestamp": "2026-06-01T14:23:07Z", "agent": "agent-42", "endpoint": "/v1/infrastructure/query", "provider": "aws", "cost_estimate": 29.95, "response_ms": 187, "status": "success", "guardrails": "all_passed" }

"I need Postgres in AWS, under $50/mo"

Normalizes options across every cloud, ranks by cost

Terraform + CLI + cost estimate as one JSON payload

Budget, region, compliance, and security checks

Execution kit returned to the agent, ready to run

Your agent needs to provision infra on the fly. Synlake gives it a single API to query, compare, and get deploy-ready code across any cloud.

Automate infrastructure decisions for your agent platform. Normalized data, cost guardrails, and audit trails out of the box.

Embed cloud provisioning into your product. Your users or agents get multi-cloud infrastructure without you building the abstraction layer.

This hits the real Synlake API. Configure your requirements and get a full execution payload back.

You could wire up each cloud yourself. Here's why teams choose Synlake.

100 free API calls every month. No credit card required.

✓ Cost estimates
✓ Multi-cloud comparison
✓ Terraform HCL + CLI
✓ No credit card required

$0.01 — estimate
$0.05 — query (basic)
$0.10 — query + execution kit
$0.05 — validate (dry-run)

Spending caps— set a monthly limit per agent. Synlake blocks requests when the cap is reached. Zero surprise bills.

Deploy and operate workloads, secrets, and networking across AWS, GCP, Azure, and private clouds.

Manage virtual machines across multiple cloud providers, including AWS EC2, Azure Virtual Machines, and GCP Compute Engine.

An MCP server for managing Red Hat OpenShift clusters via the OCM API.

Manage cloud infrastructure using Pulumi's Infrastructure as Code (IaC) platform. Requires the Pulumi CLI to be installed.

MCP server to query and govern your AWS, GCP & Azure cloud estate (and AI runtimes like Bedrock & Vertex AI) from Claude Code or Cursor surfaces waste, cost, ownership, and 400+ audit findings across 200+ resource types.

Get prescriptive CDK advice, explain CDK Nag rules, check suppressions, generate Bedrock Agent schemas, and discover AWS Solutions Constructs patterns.

Core AWS MCP server providing prompt understanding and server management capabilities.

Manage and interact with Microsoft Azure services.

An MCP Server that connects to Gemini Cloud Assist APIs, enabling you to manage and troubleshoot your Google Cloud environment using natural language.

Enables AI assistants to interact with Azure Kubernetes Service (AKS) clusters.