Sold by: Chaos Gears
MCP (Model Context Protocol) is the open, vendor-neutral “USB-C for agents” — a single plug-and-play way for Claude, Amazon Q, Cursor and any other MCP-aware client to reach your SaaS securely and invoke its tools.
We implement the MCP logic using the official open-source libraries, add sample “tools”, run integration tests against Claude & OpenAI Agents SDK, and hand over code, IaC and docs so you can run it in production on your own.
Overview
What is MCP?
The Model Context Protocol (MCP) is an open standard introduced in late 2024 that acts as a universal interface for connecting AI agents to external systems, just like USB‑C works across hardware. MCP standardizes how models discover tools, fetch data, and interact with services securely and dynamically.
Many SaaS applications want to be used more by AI agents—but each agent (Claude, Amazon Q, Cursor, etc.) typically requires a unique connector. MCP Server on AWS solves this by enabling your product to be an MCP server: your SaaS exposes its API/functions through a standard MCP interface. Once built, your product becomes plug-and-play for any agent using the MCP protocol—no bespoke integrations needed.
It defines a JSON-based request/response schema so agents can discover capabilities, call functions and stream results just as USB-C standardises power and data lines for hardware peripherals.
Because MCP runs over HTTPS, you can host a server anywhere – including AWS cloud - without retraining the model or sending private data back to the model provider.
Why your SaaS needs it:
- Instant interoperability – Any MCP-capable agent (Claude, Amazon Q, OpenAI Agents SDK, Microsoft Copilot, etc.) can call your SaaS with zero bespoke glue code.
- More usage, less churn – Customers embed your features in agent workflows instead of abandoning the app tab.
- Future-proof – MCP is being adopted across the industry as the baseline for agent–tool communication
What we deliver
This POC includes:
- Secure, scalable deployment via AWS Fargate and Application Load Balancer, handling authentication, TLS, and MCP sessions
- Integration of open-source MCP server libraries (e.g., Python/TypeScript), customized for your API endpoints and business logic
- Implementation of MCP tool definitions – exposing functions, data fetches, document retrieval, etc.
- Comprehensive testing and validation, demonstrating Claude, Amazon Q, or Cursor calling your SaaS via MCP
- Deployment documentation and handover, enabling your team to run everything in production afterwards
You walk away with a working MCP Server running in your AWS account—fully integrated, tested, and ready for real-world agent interoperability.
Industry-ready and future-proof:
- SaaS vendors: enable your app to be embedded in AI agents without extra dev
- CRM/Collaboration platforms: deliver tools to AI agents via MCP
- Analytics/BI tools: allow agents to query datasets and perform actions dynamically
- Enterprise integrations: support internal agents (e.g., Claude for Work) to securely access your platform
Highlights
- Once built, your SaaS acts like a “USB‑C port for AI”: plug in any agent (Claude, Amazon Q, Cursor, etc.) without writing new connectors.
- Your RFC‑defined MCP Server runs on AWS Fargate with an ALB, managing security, authentication, and protocol-level scaling - ready to plug into any MCP-enabled agent.
- Agent-ready out of the box – validated against Claude, Amazon Q and OpenAI Agents SDK during the engagement.
Details
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Delivery method
Deployed on AWS
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Support
Vendor support
Tell us more about your challenges – email us at genai@chaosgears.com