5 Ways to Create an MCP Server in 2025 (Compared)

Five approaches, one goal

You want your AI agent to call an API. The Model Context Protocol (MCP) is the standard interface. But how do you actually create the server? Here are the five main approaches in 2025, ranked by speed and flexibility.

1. Traffic capture (DataFaucet)

How it works: Enter a URL. A cloud browser navigates the site, captures real API traffic, and generates typed MCP tool definitions. One-click deploy to a hosted endpoint.

Best for: Any app, especially ones without public APIs, internal tools, or services with incomplete documentation.

Time to deploy: 60 seconds.

Tradeoff: Requires the app to be browser-accessible. Purely CLI-based APIs need the cURL input method instead.

Try it free | Watch the demo

2. OpenAPI spec conversion

How it works: Feed an existing OpenAPI/Swagger spec file into a converter tool. It generates MCP server code from the endpoint definitions.

Tools: @anthropic-ai/openapi-to-mcp, openapi-mcp-codegen, nicobailon/openapi-to-mcp

Best for: Well-documented public APIs that maintain an accurate, up-to-date spec file.

Time to deploy: 5-30 minutes (find spec, run tool, configure auth, deploy).

Tradeoff: Requires a spec to exist. Many APIs have outdated or incomplete specs. You still need to self-host.

3. Docs-first generation (Mintlify)

How it works: If your API docs are hosted on Mintlify, they can auto-generate an MCP server from the documentation structure.

Best for: Teams already using Mintlify for API docs who want a zero-effort MCP layer.

Time to deploy: Minutes (if docs already exist).

Tradeoff: Locked to Mintlify platform. Only works if your docs are comprehensive and current.

4. Marketplace browse (Smithery, Glama)

How it works: Search a catalog of community-built MCP servers. Find one for your service, connect credentials, and use it.

Tools: Smithery (100K+ tools), Glama (registry with security scoring)

Best for: Popular services where a high-quality community server already exists.

Time to deploy: 2-10 minutes (find server, configure auth).

Tradeoff: Limited to what's been built. Fixed tool definitions you can't customize. Many services have no server yet.

5. Manual SDK implementation

How it works: Use the official MCP SDK (@modelcontextprotocol/sdk) to write a TypeScript/Python server from scratch. Define tools, handle requests, manage auth.

Best for: Highly custom requirements, non-HTTP integrations (databases, file systems), or when you need total control.

Time to deploy: Hours to days depending on API complexity.

Tradeoff: Requires developer time, MCP protocol knowledge, and ongoing maintenance.

Quick comparison

Which should you use?

Start with the marketplace. If a good server exists for your service, use it.

If it doesn't (or the existing one is missing endpoints you need), use DataFaucet to generate one from traffic. It's the fastest path when you need something custom.

Use OpenAPI conversion when you have a clean spec and want to self-host. Use the manual SDK when you need total control or non-HTTP integrations.

Most teams end up using a combination. Marketplace servers for common tools, DataFaucet for internal apps and custom endpoints, and manual SDK for the truly unique stuff.

Detailed comparisons

Want a deeper look at how DataFaucet stacks up against specific alternatives?

• DataFaucet vs Smithery (marketplace with 100K+ tools)
• DataFaucet vs Composio (managed integration platform)
• DataFaucet vs mcp.hosting (one-click pre-built server hosting)
• DataFaucet vs Invok (self-hosted OpenAPI-to-MCP converter)
• View all comparisons

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