ToolCenter MCP

The Swiss-Army MCP server for web tools — one install, 15 LLM-ready tools.

Give your AI agent instant access to web search, scraping, screenshots, SEO/accessibility audits, DNS/WHOIS/SSL checks, and more — all through a single Model Context Protocol server. Outputs are optimized for LLM consumption (clean Markdown, structured reports) so your agent spends tokens on reasoning, not parsing HTML soup.

Tools included

Install

1. Get an API key

Create a free account at toolcenter.dev and copy your API key from the dashboard.

2. Add to your MCP client

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "toolcenter": {
      "command": "npx",
      "args": ["-y", "toolcenter-mcp"],
      "env": {
        "TOOLCENTER_API_KEY": "tc_xxxxxxxxxxxxxxxxxxxx"
      }
    }
  }
}

Restart Claude Desktop. The 15 tools appear under the hammer icon.

Cursor

Settings → MCP → Add server:

{
  "toolcenter": {
    "command": "npx",
    "args": ["-y", "toolcenter-mcp"],
    "env": { "TOOLCENTER_API_KEY": "tc_..." }
  }
}

Claude Code (CLI)

claude mcp add toolcenter -e TOOLCENTER_API_KEY=tc_... -- npx -y toolcenter-mcp

3. (Optional) Self-host the backend

The MCP server talks to api.toolcenter.dev by default. To point at your own ToolCenter instance, set TOOLCENTER_BASE_URL:

"env": {
  "TOOLCENTER_API_KEY": "tc_...",
  "TOOLCENTER_BASE_URL": "https://api.your-domain.com"
}

Quickstart: build an agent in 5 minutes

Ask Claude:

Research the top 3 competitors of Linear.app. For each, give me their pricing page, tech stack, SEO score, and a screenshot of their homepage.

The agent will chain web_search → scrape_url → detect_tech_stack → analyze_seo → screenshot automatically. No glue code.

Development

git clone https://github.com/toolcenter-dev/mcp
cd mcp
npm install
cp .env.example .env   # add your key
npm run build
TOOLCENTER_API_KEY=tc_... node dist/index.js   # runs over stdio

Output design

Every tool returns Markdown structured for LLM consumption. For example, scrape_url runs the HTML through Mozilla Readability to strip nav/footer/ads, then converts the article body with Turndown. A 2 MB page becomes ~4 KB of Markdown — 500× fewer tokens than raw HTML.

License

MIT © 2026 ToolCenter