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.
README
Synlake MCP Server
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
- Website: synlake.ai
- Docs: synlake.ai/docs
- Source: github.com/synlake-ai/synlake
- npm: @synlake-ai/mcp-server
- MCP Registry:
ai.synlake/synlake— registry.modelcontextprotocol.io - Privacy: synlake.ai/legal/privacy.html — only what's needed to process queries. No conversation data, no profiling, no data sales.
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
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.