Mcpify

NilayYadav23stars

Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

1# Mcpify

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 23
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Mcpify?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Mcpify need an API key?

No required environment variable is listed on this record.

What transport does Mcpify use?

Mcpify runs locally over stdio.

When was Mcpify last checked?

Last checked 2026-10-28. Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

From the publisher

Documentation

mcpify

Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

Demo

What it does

mcpify watches HTTP requests to your server and automatically creates MCP tools for each discovered endpoint. AI assistants can then call these tools to interact with your APIs.

Installation

brew tap nilayyadav/mcpify
brew install mcpify

Quick Start

Start your API server (e.g., on localhost:3000)
Run mcpify to observe traffic:

sudo mcpify --target http://localhost:3000

Make API calls to your server (using your app, curl, Postman, etc.)
Each unique endpoint becomes available as an MCP tool at http://localhost:8081/mcp

Persistent Configuration

mcpify automatically saves discovered tools and configuration:

Linux: ~/.config/mcpify/config.json
macOS: ~/Library/Application Support/mcpify/config.json

Discovered tools persist across restarts. If you run mcpify without --target, it will use the last observed server.

# First run - discovers and saves tools
sudo mcpify --target http://localhost:3000

# Later runs - automatically uses saved target and loads existing tools
sudo mcpify

Grouping Feature

mcpify can now automatically group related API endpoints into logical tool groups. This makes it easier for AI assistants to understand and interact with your API by organizing endpoints by resource or functionality (e.g., all /users endpoints are grouped together).

How Grouping Works

Endpoints are analyzed and grouped based on URL patterns and HTTP methods.
Each group is exposed as a collection of related tools in the MCP server.
Grouping improves discoverability and usability for large APIs.

Grouping is enabled by default. You can control grouping behavior with the following command line flag:

sudo mcpify --target http://localhost:3000 --grouping

Grouped tools are available at http://localhost:8081/mcp as usual, but now organized by group.

Configuration

Environment Variables

export LLM="openai/gpt-oss-120b:together"
export LLM_ENDPOINT="https://router.huggingface.co/v1"
export LLM_API_KEY="HF_TOKEN"

Command Line Options

sudo -E mcpify --target http://localhost:3000 \
       --max-tools 100 \
       --use-llm \
       --verbose

Flag	Description	Default
`--target`	Target server URL to observe (uses saved target if omitted)	-
`--mcp-port`	MCP server port	`8081`
`--mcp-name`	Name of the MCP server	`mcpify`
`--max-tools`	Maximum number of tools to capture	`100`
`--use-llm`	Enable LLM for tool name generation	`false`
`--verbose`	Enable verbose logging	`false`
`--grouping`	Enable grouping of related API endpoints	`true`

Requirements

macOS or Linux
Root/sudo privileges (for packet capture)
Target server running on HTTP (not HTTPS)

MCP Integration

Connect AI assistants to http://localhost:8081/mcp to access auto-generated tools.

License

MIT

Mcpify

NilayYadav23stars

Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Mcpify

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 23
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Mcpify?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Mcpify need an API key?

No required environment variable is listed on this record.

What transport does Mcpify use?

Mcpify runs locally over stdio.

When was Mcpify last checked?

Last checked 2026-10-28. Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

From the publisher

Documentation

mcpify

Automatically generate MCP (Model Context Protocol) servers by observing HTTP API traffic.

Demo

What it does

mcpify watches HTTP requests to your server and automatically creates MCP tools for each discovered endpoint. AI assistants can then call these tools to interact with your APIs.

Installation

brew tap nilayyadav/mcpify
brew install mcpify

Quick Start

Start your API server (e.g., on localhost:3000)
Run mcpify to observe traffic:

sudo mcpify --target http://localhost:3000

Make API calls to your server (using your app, curl, Postman, etc.)
Each unique endpoint becomes available as an MCP tool at http://localhost:8081/mcp

Persistent Configuration

mcpify automatically saves discovered tools and configuration:

Linux: ~/.config/mcpify/config.json
macOS: ~/Library/Application Support/mcpify/config.json

Discovered tools persist across restarts. If you run mcpify without --target, it will use the last observed server.

# First run - discovers and saves tools
sudo mcpify --target http://localhost:3000

# Later runs - automatically uses saved target and loads existing tools
sudo mcpify

Grouping Feature

How Grouping Works

Endpoints are analyzed and grouped based on URL patterns and HTTP methods.
Each group is exposed as a collection of related tools in the MCP server.
Grouping improves discoverability and usability for large APIs.

Grouping is enabled by default. You can control grouping behavior with the following command line flag:

sudo mcpify --target http://localhost:3000 --grouping

Grouped tools are available at http://localhost:8081/mcp as usual, but now organized by group.

Configuration

Environment Variables

export LLM="openai/gpt-oss-120b:together"
export LLM_ENDPOINT="https://router.huggingface.co/v1"
export LLM_API_KEY="HF_TOKEN"

Command Line Options

sudo -E mcpify --target http://localhost:3000 \
       --max-tools 100 \
       --use-llm \
       --verbose

Flag	Description	Default
`--target`	Target server URL to observe (uses saved target if omitted)	-
`--mcp-port`	MCP server port	`8081`
`--mcp-name`	Name of the MCP server	`mcpify`
`--max-tools`	Maximum number of tools to capture	`100`
`--use-llm`	Enable LLM for tool name generation	`false`
`--verbose`	Enable verbose logging	`false`
`--grouping`	Enable grouping of related API endpoints	`true`

Requirements

macOS or Linux
Root/sudo privileges (for packet capture)
Target server running on HTTP (not HTTPS)

MCP Integration

Connect AI assistants to http://localhost:8081/mcp to access auto-generated tools.

License

MIT