MCP Tool Factory

MCP Tool Factory (TypeScript)

Generate production-ready MCP (Model Context Protocol) servers from natural language descriptions, OpenAPI specs, database schemas, GraphQL schemas, or ontologies.

Why MCP?

The Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect with external data sources and tools. MCP servers expose tools that can be used by:

• Claude Code and Claude Desktop
• OpenAI Agents SDK
• Google ADK (Agent Development Kit)
• LangChain and CrewAI
• Any MCP-compatible client

MCP Tool Factory lets you generate complete, production-ready MCP servers in seconds.

Features

Use as MCP Server

MCP Tool Factory is itself an MCP server! Add it to Claude Desktop, Claude Code, Cursor, or VS Code to generate MCP servers through conversation.

Tier 1 — Zero Config (Claude Code)

Claude Code auto-injects CLAUDE_CODE_OAUTH_TOKEN — no env vars needed:

claude mcp add mcp-tool-factory -- node /path/to/mcp-tool-factory-ts/bin/mcp-server.js

Tier 2 — Standard (Pick a Provider)

Set one API key and go. The factory auto-detects the provider:

Claude Desktop / Cursor / VS Code — add to your MCP config (claude_desktop_config.json, .cursor/mcp.json, or .vscode/mcp.json):

{

"mcpServers": { "mcp-tool-factory": { "command": "node", "args": ["/path/to/mcp-tool-factory-ts/bin/mcp-server.js"], "env": { "ANTHROPIC_API_KEY": "your-key-here" } } } }

Any of these API keys will work: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, MISTRAL_API_KEY, DEEPSEEK_API_KEY, GROQ_API_KEY, XAI_API_KEY, AZURE_OPENAI_API_KEY, COHERE_API_KEY.

Tier 3 — Full Control (Provider + Model + Budget)

Use MCP_FACTORY_PROVIDER, MCP_FACTORY_MODEL, and MCP_FACTORY_BUDGET to override auto-detection:

{

"mcpServers": { "mcp-tool-factory": { "command": "node", "args": ["/path/to/mcp-tool-factory-ts/bin/mcp-server.js"], "env": { "OPENAI_API_KEY": "your-key-here", "MCP_FACTORY_PROVIDER": "openai", "MCP_FACTORY_MODEL": "gpt-5.2", "MCP_FACTORY_BUDGET": "0.50" } } } }

Claude Code CLI with full control:

claude mcp add mcp-tool-factory \

-e DEEPSEEK_API_KEY=your-key \ -e MCP_FACTORY_PROVIDER=deepseek \ -e MCP_FACTORY_MODEL=deepseek-chat \ -e MCP_FACTORY_BUDGET=0.25 \ -- node /path/to/mcp-tool-factory-ts/bin/mcp-server.js

Available Tools

Example Conversation

You: Create an MCP server for the GitHub API with tools to list repos, create issues, and manage pull requests

Claude: *Uses generate_mcp_server tool*

I've generated a complete MCP server with the following tools:

- list_repositories - List user repositories

- create_issue - Create a new issue

- list_pull_requests - List PRs for a repo

- merge_pull_request - Merge a PR

Let me write these files to your project...

Quick Start

Installation

# Global installation

npm install -g @heshamfsalama/mcp-tool-factory

Or use npx

npx @heshamfsalama/mcp-tool-factory generate "Create tools for managing a todo list"

Set Your API Key

At least one provider API key is required:

# Anthropic Claude (recommended)

export ANTHROPIC_API_KEY=your-key-here

Or Claude Code OAuth

export CLAUDE_CODE_OAUTH_TOKEN=your-token-here

Or any other supported provider

export OPENAI_API_KEY=your-key-here export GOOGLE_API_KEY=your-key-here export MISTRAL_API_KEY=your-key-here export DEEPSEEK_API_KEY=your-key-here export GROQ_API_KEY=your-key-here export XAI_API_KEY=your-key-here export AZURE_OPENAI_API_KEY=your-key-here export COHERE_API_KEY=your-key-here

Generate Your First Server

# From natural language

mcp-factory generate "Create tools for fetching weather data by city and converting temperatures"

From OpenAPI spec

mcp-factory from-openapi ./api-spec.yaml

From database

mcp-factory from-database ./data.db

From GraphQL schema

mcp-factory from-graphql ./schema.graphql

From ontology

mcp-factory from-ontology ./ontology.owl --format rdf

Usage

Natural Language Generation

mcp-factory generate "Create tools for managing a todo list with priorities" \

--name todo-server \ --output ./servers/todo \ --web-search \ --logging \ --metrics

OpenAPI Specification

# From local file

mcp-factory from-openapi ./openapi.yaml --name my-api-server

With custom base URL

mcp-factory from-openapi ./spec.json --base-url https://api.example.com

Database Schema

# SQLite

mcp-factory from-database ./myapp.db --tables users,posts,comments

PostgreSQL

mcp-factory from-database "postgresql://user:pass@localhost/mydb" --type postgresql

GraphQL Schema

# From a GraphQL SDL file

mcp-factory from-graphql ./schema.graphql --name my-graphql-server

From a URL endpoint

mcp-factory from-graphql https://api.example.com/graphql --name my-api-server

GraphQL queries are mapped to read-only MCP tools, and mutations are mapped to write tools. GraphQL types are automatically converted to Zod validation schemas.

Ontology

# From RDF/OWL (.owl, .rdf, .ttl)

mcp-factory from-ontology ./ontology.owl --format rdf --name knowledge-server

From JSON-LD (.jsonld)

mcp-factory from-ontology ./schema.jsonld --format jsonld --name linked-data-server

From custom YAML ontology

mcp-factory from-ontology ./domain.yaml --format yaml --name domain-server

OWL Classes are mapped to MCP Resources, ObjectProperties become Tools, and DataProperties become tool parameters.

Test & Serve

# Run tests

mcp-factory test ./servers/my-server

Start server for testing

mcp-factory serve ./servers/my-server

Generated Server Structure

servers/my-server/

├── src/ │ └── index.ts # MCP server with tools, resources, and prompts ├── tests/ │ └── tools.test.ts # Vitest tests (InMemoryTransport) ├── package.json # Dependencies ├── tsconfig.json # TypeScript config ├── Dockerfile # Container deployment ├── README.md # Usage documentation ├── skill.md # Claude Code skill file ├── server.json # MCP Registry manifest ├── EXECUTION_LOG.md # Generation trace (optional) └── .github/ └── workflows/ └── ci.yml # GitHub Actions CI/CD

Generated servers export a createServer() factory function for easy testing. The server uses Streamable HTTP transport with a single /mcp POST endpoint and a /health GET endpoint. Tests use InMemoryTransport.createLinkedPair() for fast, reliable in-process testing with vitest.

CLI Reference

Generate Options

mcp-factory generate "..." \

--output, -o # Output directory (default: ./servers) --name, -n # Server name --description, -d # Package description --github-username, -g # GitHub username for MCP Registry --version, -v # Server version (default: 1.0.0) --provider, -p # LLM provider (anthropic, openai, google, mistral, deepseek, groq, xai, azure, cohere, claude_code) --model, -m # Specific model to use --web-search, -w # Search web for API documentation --auth # Environment variables for auth --health-check # Include health check endpoint (default: true) --logging # Enable structured logging (default: true) --metrics # Enable Prometheus metrics --rate-limit # Rate limiting (requests per minute) --retries # Enable retry logic (default: true) --budget # Maximum spend in USD (aborts if exceeded) --compare-costs # Show cost comparison across providers before generating

Configuration

Environment Variables

| GOOGLE_API_KEY | Google Gemini API key | for generat