Synlake MCP Server

Synlake MCP Server

Enables AI agents to discover, evaluate, and provision cloud infrastructure across AWS, GCP, and Azure with cross-cloud normalization, cost comparisons, and deployable execution kits.

Category
Visit Server

README

Synlake MCP Server

npm MCP Registry License: MIT

The MCP connector for Synlake — B2AI infrastructure for autonomous agents. Synlake normalizes AWS, GCP, and Azure into one schema, generates ready-to-run execution kits (Terraform HCL + CLI), and prices them before deploy — so an AI agent can discover, evaluate, and provision cloud infrastructure with zero human intervention.

This repository is the open-source MCP server (a thin stdio ↔ HTTP proxy). The infrastructure intelligence — cross-cloud normalization, the cost engine, and execution-kit generation — runs as a hosted service at api.synlake.ai.

🌐 synlake.ai · 📖 Docs · 🔌 MCP: ai.synlake/synlake


An agent deploys infrastructure — no human in the loop

A coding agent needs a Kubernetes node pool. It doesn't open a cloud console, compare pricing pages, or hand-write Terraform. It asks Synlake, and gets back a deployable answer:

Agent → Synlake:  "compute, 4 vCPUs, 16 GB RAM, us-east-1, budget $100/mo"

Synlake → Agent:  best:  gcp · e2-standard-4 · $97.82/mo   (19.5% cheaper than the priciest)
                  also:  aws t3.xlarge $121.47 · azure Standard_B4ms $121.18
                  kit:   { terraform: "resource \"google_compute_instance\"…",
                           cli: "gcloud compute instances create…" }
                  ✓ validated: no public ingress, encryption on, within budget

The agent reviews the kit, applies the Terraform, and moves on. Every response is dense, deterministic JSON — built for machine consumption, not dashboards. Synlake tools are read-only: they recommend, price, and validate. A human (or the agent's own policy) runs the execution kit.

Architecture

flowchart LR
    A[AI Agent] -- MCP / REST --> B[Synlake API]
    B --> C[Normalizer]
    C --> D1[AWS adapter]
    C --> D2[Azure adapter]
    C --> D3[GCP adapter]
    C --> E[Ranking engine<br/>cost + constraints]
    E --> F[Execution-kit generator<br/>Terraform + CLI]
    F --> G[Guardrails & validation<br/>budget · region · security]
    G --> H[Audit log]
    H --> A

An agent sends an intent. Synlake normalizes options across clouds, ranks them by cost and constraints, generates a deploy-ready execution kit, runs guardrail checks, logs the call, and returns one machine-ready payload. This repo ships the open-source MCP connector (the AI Agent ↔ Synlake API edge); the boxes to the right of Synlake API run as the hosted service.

Quickstart

Hosted (recommended) — MCP over Streamable HTTP

Point any MCP client at the hosted server — three lines, nothing to install:

{
  "mcpServers": {
    "synlake": {
      "url": "https://api.synlake.ai/api/mcp",
      "headers": { "Authorization": "Bearer sk_synlake_YOUR_KEY" }
    }
  }
}

Local stdio wrapper (this package)

For clients that speak stdio (e.g. Claude Desktop), run the npm wrapper — it proxies to the same hosted server:

{
  "mcpServers": {
    "synlake": {
      "command": "npx",
      "args": ["-y", "@synlake-ai/mcp-server"],
      "env": { "SYNLAKE_API_KEY": "sk_synlake_YOUR_KEY" }
    }
  }
}

Get a free API key at synlake.ai (100 calls/month, no card required). The estimate endpoint is even callable without a key — zero friction to try.

Tools

Tool REST endpoint Description
synlake_query POST /v1/infrastructure/query Full recommendation + execution kit (Terraform + CLI)
synlake_estimate POST /v1/infrastructure/estimate Cross-cloud cost comparison — no API key required
synlake_validate POST /v1/execution/validate Dry-run an execution kit (security + budget checks)
synlake_providers GET /v1/providers List supported providers and services
synlake_usage GET /v1/agent/usage Your usage, costs, and spending cap

Full reference (OpenAPI 3.1, rendered): synlake.ai/docs. Local copy: docs/openapi.yaml. Machine-readable summary for agents: synlake.ai/llms.txt.

Why Synlake

Approach Multi-cloud Agent-ready JSON Execution kit Cost guardrails Audit trail
DIY Terraform Manual No You write it No No
Pulumi / Crossplane Yes No Partial No Partial
Cloud provider SDKs Single Partial No No Partial
Agent frameworks Via tools Partial No No No
Synlake 3 clouds 100% Full kit Built-in Every call

Use it from a Claude Managed Agent

Wire Synlake as an mcp_toolset — the agent gets all five tools natively, your key stays in an Anthropic vault:

{
  "type": "mcp_toolset",
  "name": "synlake",
  "server": {
    "url": "https://api.synlake.ai/api/mcp",
    "authorization_token": { "vault_secret": "synlake_api_key" }
  }
}

See the MCP quickstart for the Managed Agents API, ant CLI, and Agent SDK flows.

Build from source

npm install
npm run build       # tsc → dist/ (pure proxy)
SYNLAKE_API_KEY=sk_synlake_... node dist/bin.js

SYNLAKE_API_URL overrides the remote endpoint (default https://api.synlake.ai/api/mcp).

Pricing

Pay per call. No subscriptions, no commitments. Free tier: 100 calls/month, no card required.

Call type Price
Estimate $0.01 (free, no key, IP rate-limited)
Query (basic) $0.05
Query (full + Terraform) $0.10
Validate $0.05

Links

License

The MCP connector in this repository is MIT licensed (see LICENSE). The Synlake service (api.synlake.ai) — the cost engine, cross-cloud normalization, and execution-kit generation — is proprietary.

El conector MCP de este repo es MIT. El servicio Synlake (api.synlake.ai) es propietario.

© Synlake, LLC — admin@synlake.ai

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured