Which integrations are available for this server?

Enables interaction with the GitHub REST API by parsing its documentation and generating tool definitions for endpoints like users and other resources. Enables interaction with the Stripe API by parsing its documentation and automatically generating tool definitions for its financial and payment services.

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCPify Create an MCP server for the Stripe API using https://stripe.com/docs/api" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCPify

Point it at API docs, get an MCP server.

MCPify scrapes API documentation, uses Gemini to figure out the endpoints/auth/params, and spits out a config file. The runtime reads that config and runs an MCP server that Claude (or any MCP client) can use to call the API.

Installation

git clone https://github.com/yourusername/mcpify.git cd mcpify pip install -e .

Needs Python 3.11+ and a Gemini API key.

Usage

export GEMINI_API_KEY="your-api-key" # Parse docs into a config file mcpify parse https://api.example.com/docs -o my-api.json # Run the server mcpify serve my-api.json --auth "your-api-token" # Or do both at once mcpify quickstart https://api.example.com/docs --auth "token"

To use with Claude Desktop, add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{ "mcpServers": { "my-api": { "command": "mcpify", "args": ["serve", "/path/to/my-api.json", "--auth", "your-token"] } } }

CLI

mcpify parse <url> - Scrape docs and generate config

mcpify parse https://docs.github.com/en/rest -o github.json --max-pages 15

Option	Description
`-o, --output`	Output file (default: `mcpify-config.json`)
`-m, --max-pages`	Max pages to scrape (default: 10)
`--no-follow`	Don't follow links
`-k, --api-key`	Gemini API key (or use env var)
`--model`	Gemini model (default: `gemini-2.0-flash`)

mcpify serve <config> - Run MCP server

mcpify serve my-api.json --auth "Bearer token" --transport stdio

Option	Description
`-a, --auth`	Auth token for API calls
`-t, --transport`	`stdio`, `sse`, or `http` (default: `stdio`)

mcpify show <config> - Print config as table

mcpify quickstart <url> - Parse and serve in one shot

Config Format

The generated JSON looks like this:

{ "name": "my-api", "description": "Description of the API", "base_url": "https://api.example.com/v1", "version": "1.0.0", "auth": { "type": "bearer", "header_name": "Authorization", "prefix": "Bearer " }, "tools": [ { "name": "get_users", "description": "Retrieve a list of users", "method": "GET", "path": "/users", "parameters": [ { "name": "limit", "type": "integer", "description": "Max results to return", "required": false, "location": "query", "default": 10 } ], "response": { "description": "Array of user objects" }, "tags": ["users"] } ] }

Auth types: none, api_key, bearer, oauth2

Parameter locations: query, path, header, body

Python API

from mcpify.scraper import scrape_documentation from mcpify.parser import parse_documentation from mcpify.runtime import create_mcp_server # Scrape docs docs = await scrape_documentation("https://api.example.com/docs") # Parse with Gemini config = await parse_documentation(docs) # Save config config_path = "my-api.json" with open(config_path, "w") as f: f.write(config.to_json()) # Create and run server server = create_mcp_server(config, auth_token="your-token") server.run()

Examples

# GitHub mcpify parse https://docs.github.com/en/rest/users -o github.json mcpify serve github.json --auth "ghp_your_token" # Stripe mcpify parse https://stripe.com/docs/api -o stripe.json mcpify serve stripe.json --auth "sk_test_your_key"

License

MIT

MCPify

MCPify

Installation

Usage

CLI

Config Format

Python API

Examples

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