The Model Context Protocol solves a real problem: giving AI agents a standard way to call external tools. But once you decide to use MCP, a second question shows up immediately — who runs the server?
Every MCP connector needs somewhere to live. It needs to stay online, handle authentication, store credentials safely, and respond fast enough that your AI agent doesn't time out mid-conversation. That's infrastructure — and infrastructure is exactly what most teams reaching for an AI agent do not want to own.
Self-hosted vs hosted MCP
Self-hosted MCP means you write or download the connector code, provision a server (a VPS, a container platform, a serverless function), deploy it, and keep it running. You own uptime, security patches, credential storage, and scaling. This is the right call if you have specific compliance requirements that demand the server sit entirely inside your own network.
Hosted MCP means someone else runs that server for you. You get an endpoint — a URL and an API key — and a dashboard to manage which connectors are active. You never provision a machine, patch an OS, or debug why a container restarted at 3am.
What a hosted MCP endpoint actually looks like
In practice, a hosted MCP platform gives you one URL that represents every API you've connected:
https://mcp.yourplatform.com/your-account/sse
You paste that single endpoint into Claude Desktop, Cursor, or any MCP-compatible agent once. From then on, every connector you activate — SAP, GitHub, Salesforce, Stripe, or a custom internal API — becomes available to that same agent through that same URL. Add a connector in the dashboard, and it shows up on the endpoint immediately. No redeploy, no new config.
The part people underestimate: credentials
Every connector needs a credential — an API key, an OAuth token, a database connection string, SAP login details. Storing these safely is not trivial: they need to be encrypted at rest, isolated per account, and never logged or returned by any API response. Get this wrong and a single leaked credential can expose a production system.
A hosted platform takes this on as its job. Credentials go into an isolated, encrypted vault the moment you enter them, and the platform only decrypts them momentarily, server-side, at the exact instant a tool call needs them.
When self-hosting is still the right call
- →Regulatory requirements mandate zero external network egress for a specific system
- →You already have dedicated platform engineering capacity and want full control
- →You're connecting a single internal API with no plans to add more
Outside of those cases, hosted MCP is almost always faster to get running and cheaper to maintain than standing up your own server — you're trading a small monthly fee for the engineering time you'd otherwise spend on uptime, patching, and credential security.
What to look for in a hosted MCP platform
- ✓A real connector catalogue, not just a bare protocol implementation
- ✓A way to bring your own API when the catalogue doesn't cover something
- ✓Per-account credential isolation, not a shared credential store
- ✓A log of every tool call — what was called, with what input, and what came back
- ✓No lock-in to a single AI model — Claude, GPT-4, and Gemini should all work the same way
Get a hosted MCP endpoint in minutes
Episteme Protocol hosts your MCP endpoint and gives you a catalogue of connectors — SAP, Salesforce, GitHub, Stripe, and more — plus a builder for anything else. No servers to manage.
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