mcpboot

mcpboot

Generates and serves an MCP server from a natural language prompt, without requiring SDK knowledge or boilerplate code.

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mcpboot

Generate and serve an MCP server from a natural language prompt.

Point mcpboot at API documentation (or just describe what you want), and it generates a working MCP server. No SDK knowledge required. No boilerplate. No code to maintain.

The LLM is used only at startup for code generation. At runtime, tool calls execute cached JavaScript with no LLM involvement and no per-call API costs.

Installation

npm install -g mcpboot

Requires Node.js 18+.

Quick Start

# Set your LLM API key
export ANTHROPIC_API_KEY=sk-ant-...

# Generate an MCP server for the Hacker News API
mcpboot --prompt "Create MCP tools for the Hacker News API: https://github.com/HackerNews/API"

mcpboot fetches the API docs, generates tool handlers, and starts serving on http://localhost:8000/mcp.

Usage

mcpboot [options]

Options:
  --prompt <text>              Generation prompt (inline)
  --prompt-file <path>         Generation prompt from file

  --provider <name>            LLM provider: anthropic | openai (default: anthropic)
  --model <id>                 LLM model ID (default: provider-specific)
  --api-key <key>              LLM API key (env: ANTHROPIC_API_KEY | OPENAI_API_KEY)

  --port <number>              HTTP server port (default: 8000)
  --cache-dir <path>           Cache directory (default: .mcpboot-cache)
  --no-cache                   Disable caching, regenerate on every startup
  --verbose                    Verbose logging (structured JSON to stderr)
  --log-file <path>            Write full verbose log to file (JSON lines, untruncated)
  --dry-run                    Show generation plan without starting server

Examples

# Wrap the Hacker News API
mcpboot --prompt "Create MCP tools for the Hacker News API: https://github.com/HackerNews/API"

# Wrap an API from an OpenAPI spec
mcpboot --prompt "Create MCP tools from https://petstore.swagger.io/v2/swagger.json"

# Create specific tools from a known API
mcpboot --prompt "Using the GitHub REST API (https://docs.github.com/en/rest), \
  create tools for listing repos, creating issues, and searching code"

# Create utility tools (no external API needed)
mcpboot --prompt "Create tools for JSON manipulation: pretty-print, validate, diff, and JSONPath extraction"

# Complex prompt from file
mcpboot --prompt-file ./my-api-prompt.txt --port 9000

# Preview what would be generated
mcpboot --prompt "Create MCP tools for https://github.com/HackerNews/API" --dry-run

Walkthrough: Hacker News API

Here's a complete example of generating an MCP server for the Hacker News API.

1. Start mcpboot:

mcpboot --model claude-haiku-4-5 --port 8100 --verbose \
  --prompt "Create MCP tools for the Hacker News API. The API docs are at
    https://github.com/HackerNews/API . Figure out what tools are appropriate
    to expose — things like getting top stories, new stories, getting an item
    by ID, getting a user profile, etc."

mcpboot fetches the API docs from GitHub, uses the LLM to plan and compile 10 tools, and starts serving:

[mcpboot] Found 1 URL(s) in prompt
[mcpboot] Fetched 1 page(s)
[mcpboot] Cache miss — generating tools via LLM
[mcpboot] Plan: 10 tool(s)
[mcpboot] Compiled 10 handler(s)
[mcpboot] Listening on http://localhost:8100/mcp
[mcpboot] Serving 10 tool(s)

With --verbose, each step also emits structured JSON events to stderr — one JSON object per line — with timestamps, request correlation IDs, and detailed payloads:

{"ts":"...","event":"llm_call_start","req_id":"startup","call_id":1,"provider":"anthropic","model":"claude-haiku-4-5",...}
{"ts":"...","event":"llm_call_end","req_id":"startup","call_id":1,"elapsed_ms":2100,"prompt_tokens":1240,"completion_tokens":892,...}

Use --log-file mcpboot.log to capture the full untruncated output (stderr truncates long strings to 500 chars).

2. Test with the MCP Inspector:

npx @modelcontextprotocol/inspector --transport http --server-url http://localhost:8100/mcp

Or test from the CLI with mcporter:

# List all generated tools
npx mcporter list http://localhost:8100/mcp --schema --allow-http

# Get the top 5 stories (returns story IDs)
npx mcporter call 'http://localhost:8100/mcp.get_top_stories' limit=5 --allow-http

# Fetch details for a story
npx mcporter call 'http://localhost:8100/mcp.get_item_by_id' item_id=42345678 --allow-http

# Look up a user profile
npx mcporter call 'http://localhost:8100/mcp.get_user_profile' username=dang --allow-http

Generated tools: get_top_stories, get_new_stories, get_best_stories, get_ask_stories, get_show_stories, get_job_stories, get_item_by_id, get_user_profile, get_max_item_id, get_recent_changes

Subsequent runs with the same prompt skip the LLM entirely and start instantly from cache.

Connecting from an MCP Host

Once mcpboot is running, connect any MCP-compatible host to http://localhost:8000/mcp. For example, in Claude Desktop's config:

{
  "mcpServers": {
    "my-api": {
      "url": "http://localhost:8000/mcp"
    }
  }
}

How It Works

mcpboot follows a two-phase startup, then serves tools at runtime:

Startup (LLM-assisted):

  1. Fetch — Extract URLs from the prompt, fetch their content (API docs, READMEs, OpenAPI specs), and build a domain whitelist for runtime network access.
  2. Plan — Send the prompt and fetched docs to the LLM, which produces a structured generation plan: what tools to create, their schemas, which API endpoints they use.
  3. Compile — Send each planned tool back to the LLM, which generates a JavaScript handler function that calls the API, parses responses, and formats results.
  4. Cache — Store the plan and compiled handlers on disk, keyed by prompt hash + content hash. Subsequent startups with the same prompt and unchanged docs skip the LLM entirely.

Runtime (no LLM):

  1. Serve — Expose the generated tools as an MCP server over StreamableHTTP. Tool calls execute the cached JavaScript handlers in a sandboxed vm with fetch access restricted to whitelisted domains.
Prompt + API Docs
       │
       ▼
  URL Fetcher ──► Planner (LLM) ──► Compiler (LLM) ──► Cache
                                                          │
                                                          ▼
  MCP Host ◄──► Exposed Server ◄──► Executor ◄──► Sandbox (vm + fetch)
                                                          │
                                                          ▼
                                                    External APIs

Security Model

Generated handlers run in a Node.js vm sandbox with:

  • Allowed: Standard JS globals, fetch (whitelisted domains only), URL, URLSearchParams
  • Blocked: require, import, process, fs, net, child_process
  • Timeout: 30 seconds per tool call

The domain whitelist is constructed automatically from URLs in the prompt and URLs discovered in the fetched documentation.

Comparison with mcpblox

mcpboot and mcpblox are complementary:

mcpblox mcpboot
Input Existing MCP server + transform prompt Natural language prompt + optional API docs
Output Transformed MCP server New MCP server from scratch
LLM generates Transform functions (input/output mappers) Tool handler functions (full API integrations)
Use case Customize an existing server Create a server that doesn't exist yet

They can be chained: use mcpboot to bootstrap a server, then mcpblox to transform it.

# Bootstrap an MCP server for the HN API
mcpboot --prompt "Create MCP tools for https://github.com/HackerNews/API" --port 8001

# Transform it with mcpblox to add higher-level tools
mcpblox --upstream-url http://localhost:8001/mcp \
  --prompt "Create a 'daily_digest' tool that gets top 10 stories with their top comments" \
  --port 8002

Development

# Install dependencies
npm install

# Run tests
npm test

# Build
npm run build

# Run from source
npx tsx src/index.ts --prompt "..."

License

Apache-2.0

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