Vestibule

Vestibule

A plugin-based MCP server that securely exposes custom tools to AI agents, keeping sensitive information hidden while enabling operations like email whitelisting through pluggable plugins.

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README

Vestibule

v0.1.0 Beta — Initial release. Installation via uv from source (not yet on PyPI).

A plugin-based MCP (Model Context Protocol) server using pluggy for extensibility.

Overview

Vestibule provides a secure way to expose custom tools to AI agents while keeping sensitive information (credentials, email addresses, API keys) hidden from the agent. Plugins implement email whitelisting, calendar access, and other sensitive operations behind clean tool interfaces.

Think of it as a gateway between AI and action — the vestibule controls what passes through, ensuring only safe, validated operations proceed.

Features

  • Plugin Architecture: Discover and load plugins via entry points
  • Secrets Management: Environment-based secrets with plugin-declared prefixes
  • TOML Configuration: Multi-level config merging (CLI > project > user > defaults)
  • Pydantic Validation: Plugin configs validated against declared schemas at startup
  • Fail-Fast: Server exits with clear errors if config or secrets validation fails
  • MCP Protocol: Full support for tools, resources, and prompts
  • Dual Transport: Stdio and HTTP/SSE transports

Quick Start

Installation

Vestibule 0.1.0 is not yet published to PyPI. Install from source using uv:

# Clone the repository
git clone https://github.com/b34nst4lk/vestibule.git
cd vestibule

# Install the server and workspace plugins
uv sync

This installs:

  • vestibule — the core MCP server
  • vestibule-email — email whitelisting plugin (workspace only)
  • vestibule-example — minimal example plugin for plugin authors

Note: The vestibule-email plugin is included as a workspace package for testing. A standalone PyPI package will be available in a future release. The vestibule-example plugin demonstrates the plugin API but is not published to PyPI.

Configuration

Create .vestibule/config.toml:

[tool.vestibule]
host = "localhost"
port = 8080
transport = "stdio"

[tool.vestibule.plugins.email]
smtp_host = "smtp.gmail.com"
sender_email = "you@gmail.com"

[tool.vestibule.plugins.email.whitelist]
alice = "alice@example.com"
bob = "bob@example.com"

Set environment variables (or use .env):

EMAIL_SMTP_PASSWORD=your_app_password
EMAIL_SENDER_EMAIL=you@gmail.com
EMAIL_WHITELIST='{"alice": "alice@example.com", "bob": "bob@example.com"}'

Running

# Run with stdio transport (for MCP clients)
uv run python main.py

# Or use the CLI
vestibule serve

Available Plugins

vestibule-email (workspace only)

Email whitelisting plugin that allows sending emails only to pre-approved recipients.

Tools:

  • send_email(recipient_name, subject, body, cc_recipient_name) - Send an email
  • list_whitelist() - List all whitelisted recipients
  • add_to_whitelist(name, email) - Add a recipient to the runtime whitelist

Note: This plugin is included as a workspace package for testing. A standalone PyPI package will be available in a future release.

vestibule-example

Minimal example plugin demonstrating the Vestibule plugin API. Use this as a template for creating your own plugins.

Tools:

  • list_whitelist() - List all whitelisted recipients
  • add_to_whitelist(name, email) - Add a recipient to the runtime whitelist
  • remove_from_whitelist(name) - Remove a recipient from the runtime whitelist

Note: This plugin is included for plugin authors as a template. It is not published to PyPI — only the vestibule server is released. See packages/vestibule_example/README.md for the plugin author guide.

Plugin Development

Creating a Plugin

  1. Create a new package with entry point:
# pyproject.toml
[project.entry-points."vestibule.plugins"]
my-plugin = "vestibule_my_plugin"
  1. Implement hooks in __init__.py:
from vestibule import hooks
from pydantic import BaseModel

@hooks.hookimpl
def vestibule_register_plugin_info():
    return "my-plugin", hooks.PluginMetadata(
        name="my-plugin",
        version="1.0.0",
        description="My custom plugin"
    )

@hooks.hookimpl
def vestibule_config_schema():
    return MyPluginConfig  # Pydantic model

@hooks.hookimpl
def vestibule_register_tools(mcp_server):
    @mcp_server.tool()
    def my_tool(arg: str) -> str:
        return f"Result: {arg}"

Available Hooks

Hook Purpose First Result
vestibule_register_plugin_info Return plugin metadata Yes
vestibule_register_tools Register MCP tools No
vestibule_register_resources Register MCP resources No
vestibule_register_prompts Register MCP prompts No
vestibule_validate_secrets Validate required secrets No
vestibule_config_schema Return Pydantic config schema Yes
vestibule_init Initialize plugin with validated config No

Project Structure

vestibule/
  vestibule/                 # Core server package
    __init__.py
    hooks.py                  # Pluggy hook specifications
    plugin_manager.py         # Plugin discovery and loading
    config.py                 # Configuration loading
    cli.py                    # CLI commands
    transports/
      stdio.py                # Stdio transport
      http_sse.py             # HTTP/SSE transport
      common.py               # Shared handlers
  packages/
    vestibule_email/         # Email whitelisting plugin
      vestibule_email/
        __init__.py
      tests/
  tests/                      # Server tests
  .vestibule/
    config.toml.example       # Example configuration
  .env.example                # Example environment variables

Commands

# Run tests
uv run pytest

# Run with coverage
uv run pytest --cov=vestibule --cov=packages/vestibule_email

# Run the server
uv run python main.py

# CLI commands
vestibule serve              # Start the server
vestibule healthcheck        # Validate plugin secrets
vestibule plugins            # List loaded plugins
vestibule version            # Show version

License

MIT

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