Plugged.in MCP Proxy Server
by
Aggregates multiple MCP servers into a single unified interface, offering an AI playground for testing, RAG document search, real‑time notifications, and support for both STDIO and Streamable HTTP transports.
Plugged.in MCP Proxy Server Overview
What is Plugged.in MCP Proxy Server about?
The proxy acts as a middleware layer that unifies access to any number of Model Context Protocol (MCP) servers. It fetches tool, prompt, and resource definitions from the plugged.in App and routes client calls to the appropriate downstream servers, turning a fragmented AI ecosystem into a single, searchable, and manageable endpoint.
How to use Plugged.in MCP Proxy Server?
- Obtain an API key from the plugged.in App (https://plugged.in/api-keys).
- Run the proxy with npm’s npx command:
Default mode runs as a STDIO process, ideal for desktop MCP clients.npx -y @pluggedin/pluggedin-mcp-proxy@latest --pluggedin-api-key YOUR_API_KEY - Optional HTTP mode – add
--transport streamable-httpand--port <number>to expose a REST‑like endpoint. - Configure your MCP client (Claude Desktop, Cline, Cursor, etc.) to point to the proxy command or HTTP URL.
- Use built‑in tools such as
pluggedin_discover_tools,pluggedin_rag_query, andpluggedin_send_notificationdirectly from the client.
Key features of Plugged.in MCP Proxy Server
- AI Playground – test any connected MCP with Claude, Gemini, OpenAI, xAI without extra setup.
- Universal MCP compatibility – works with STDIO, SSE, and Streamable HTTP servers.
- Multi‑workspace layer – switch between different sets of server configurations instantly.
- Unified document search (RAG v2) – semantic search across AI‑generated, uploaded, and API‑sourced documents with filtering by model, tags, date, and visibility.
- AI Document Exchange – MCP servers can create, version, and manage library documents with full model attribution.
- Real‑time notifications – send and receive alerts, optional email delivery.
- OAuth token handling – automatic token retrieval and refresh for protected HTTP MCP servers.
- Docker support – ready‑to‑run container with both STDIO and HTTP modes.
- Security hardening – SSRF protection, command allow‑listing, rate limiting, and input sanitization.
Use cases of Plugged.in MCP Proxy Server
- Enterprise AI orchestration – centralize dozens of specialized MCP servers (databases, file systems, custom APIs) behind one endpoint for downstream AI agents.
- Rapid prototyping – developers can spin up the proxy locally, test tools in the built‑in playground, and iterate without configuring each server individually.
- Document‑enhanced retrieval – augment LLM queries with enterprise knowledge bases using RAG v2, filtering by model provenance for compliance.
- Cross‑workspace management – teams can maintain separate MCP configurations (e.g., dev vs. prod) and switch with a single click.
- Notification pipelines – trigger Slack, email, or internal alerts from AI tool executions via the notification tool.
FAQ from the Plugged.in MCP Proxy Server
Q: Do I need to install anything besides Node.js?
A: No. The proxy is delivered as an npm package; running it with npx downloads the binary on‑the‑fly.
Q: Can I run the proxy behind a firewall?
A: Yes. Use the Streamable HTTP mode with --require-api-auth and supply a bearer token for each request.
Q: How does discovery caching work?
A: pluggedin_discover_tools first returns cached tool lists (<1 s). A background refresh updates the cache if force_refresh:true is supplied or when no cache exists.
Q: What transport should I choose? A: STDIO is simplest for desktop clients. HTTP mode is required for remote integrations, container deployments, or when you need explicit port exposure.
Q: Is there a way to limit which tools are exposed? A: Tools are filtered per workspace configuration in the plugged.in App; only the enabled server‑side tools are advertised to the client.
Q: How are documents versioned? A: Each AI‑generated document stores a SHA‑256 hash of its content, model metadata, and a parent reference for previous versions, enabling full history tracking.
Q: Are there any licensing concerns? A: The project is released under the MIT License, allowing free commercial and private use.
Plugged.in MCP Proxy Server's README
plugged.in MCP Proxy Server
📋 Overview
The plugged.in MCP Proxy Server is a powerful middleware that aggregates multiple Model Context Protocol (MCP) servers into a single unified interface. It fetches tool, prompt, and resource configurations from the plugged.in App and intelligently routes requests to the appropriate underlying MCP servers.
This proxy enables seamless integration with any MCP client (Claude, Cline, Cursor, etc.) while providing advanced management capabilities through the plugged.in ecosystem.
⭐ If you find this project useful, please consider giving it a star on GitHub! It helps us reach more developers and motivates us to keep improving.
✨ Key Features
🚀 Core Capabilities
- Built-in AI Playground: Test your MCPs instantly with Claude, Gemini, OpenAI, and xAI without any client setup
- Universal MCP Compatibility: Works with any MCP client including Claude Desktop, Cline, and Cursor
- Multi-Server Support: Connect to STDIO, SSE, and Streamable HTTP MCP servers
- Dual Transport Modes: Run proxy as STDIO (default) or Streamable HTTP server
- Unified Document Search: Search across all connected servers with built-in RAG capabilities
- AI Document Exchange (RAG v2): MCP servers can create and manage documents in your library with full attribution
- Notifications from Any Model: Receive real-time notifications with optional email delivery
- Multi-Workspace Layer: Switch between different sets of MCP configurations with one click
- API-Driven Proxy: Fetches capabilities from plugged.in App APIs rather than direct discovery
- Full MCP Support: Handles tools, resources, resource templates, and prompts
- Custom Instructions: Supports server-specific instructions formatted as MCP prompts
🎯 New in v1.5.0 (RAG v2 - AI Document Exchange)
- AI Document Creation: MCP servers can now create documents directly in your library
- Full model attribution tracking (which AI created/updated the document)
- Version history with change tracking
- Content deduplication via SHA-256 hashing
- Support for multiple formats: MD, TXT, JSON, HTML, PDF, and more
- Advanced Document Search: Enhanced RAG queries with AI filtering
- Filter by AI model, provider, date range, tags, and source type
- Semantic search with relevance scoring
- Automatic snippet generation with keyword highlighting
- Support for filtering:
ai_generated,upload, orapisources
- Document Management via MCP:
- Set document visibility: private, workspace, or public
- Parent-child relationships for document versions
- Profile-based organization alongside project-based scoping
- Real-time progress tracking for document processing
🎯 Features from v1.4.0 (Registry v2 Support)
- OAuth Token Management: Seamless OAuth authentication handling for Streamable HTTP MCP servers
- Automatic token retrieval from plugged.in App
- Secure token storage and refresh mechanisms
- No client-side authentication needed
- Enhanced Notification System: Bidirectional notification support
- Send notifications to plugged.in App
- Receive notifications from MCP servers
- Mark notifications as read/unread
- Delete notifications programmatically
- Trending Analytics: Real-time activity tracking
- Every tool call is logged and tracked
- Contributes to trending server calculations
- Usage metrics and popularity insights
- Registry Integration: Full support for Registry v2 features
- Automatic server discovery from registry
- Installation tracking and metrics
- Community server support
📦 Features from v1.1.0
- Streamable HTTP Support: Full support for downstream MCP servers using Streamable HTTP transport
- HTTP Server Mode: Run the proxy as an HTTP server with configurable ports
- Flexible Authentication: Optional Bearer token authentication for HTTP endpoints
- Session Management: Choose between stateful (session-based) or stateless operation modes
🎯 Core Features from v1.0.0
- Real-Time Notifications: Track all MCP activities with comprehensive notification support
- RAG Integration: Support for document-enhanced queries through the plugged.in App
- Inspector Scripts: Automated testing tools for debugging and development
- Health Monitoring: Built-in ping endpoint for connection monitoring
🔧 Tool Categories
The proxy provides two distinct categories of tools:
🔧 Static Built-in Tools (Always Available)
These tools are built into the proxy and work without any server configuration:
pluggedin_discover_tools- Smart discovery with caching for instant resultspluggedin_rag_query- RAG v2 search across your documents with AI filtering capabilitiespluggedin_send_notification- Send notifications with optional email deliverypluggedin_create_document- (Coming Soon) Create AI-generated documents in your library
⚡ Dynamic MCP Tools (From Connected Servers)
These tools come from your configured MCP servers and can be turned on/off:
- Database tools (PostgreSQL, SQLite, etc.)
- File system tools
- API integration tools
- Custom tools from any MCP server
The discovery tool intelligently shows both categories, giving AI models immediate access to all available capabilities.
🚀 Discovery Tool Usage
# Quick discovery - returns cached data instantly
pluggedin_discover_tools()
# Force refresh - shows current tools + runs background discovery
pluggedin_discover_tools({"force_refresh": true})
# Discover specific server
pluggedin_discover_tools({"server_uuid": "uuid-here"})
Example Response:
## 🔧 Static Built-in Tools (Always Available):
1. **pluggedin_discover_tools** - Smart discovery with caching
2. **pluggedin_rag_query** - RAG v2 search across documents with AI filtering
3. **pluggedin_send_notification** - Send notifications
4. **pluggedin_create_document** - (Coming Soon) Create AI-generated documents
## ⚡ Dynamic MCP Tools (8) - From Connected Servers:
1. **query** - Run read-only SQL queries
2. **generate_random_integer** - Generate secure random integers
...
📚 RAG v2 Usage Examples
The enhanced RAG v2 system allows MCP servers to create and search documents with full AI attribution:
# Search for documents created by specific AI models
pluggedin_rag_query({
"query": "system architecture",
"filters": {
"modelName": "Claude 3 Opus",
"source": "ai_generated",
"tags": ["technical"]
}
})
# Search across all document sources
pluggedin_rag_query({
"query": "deployment guide",
"filters": {
"dateFrom": "2024-01-01",
"visibility": "workspace"
}
})
# Future: Create AI-generated documents (Coming Soon)
pluggedin_create_document({
"title": "Analysis Report",
"content": "# Market Analysis\n\nDetailed findings...",
"format": "md",
"tags": ["analysis", "market"],
"metadata": {
"model": {
"name": "Claude 3 Opus",
"provider": "Anthropic"
}
}
})
🚀 Quick Start
Prerequisites
- Node.js 18+ (recommended v20+)
- An API key from the plugged.in App (get one at plugged.in/api-keys)
Installation
# Install and run with npx (latest v1.0.0)
npx -y @pluggedin/pluggedin-mcp-proxy@latest --pluggedin-api-key YOUR_API_KEY
🔄 Upgrading to v1.0.0
For existing installations, see our Migration Guide for detailed upgrade instructions.
# Quick upgrade
npx -y @pluggedin/pluggedin-mcp-proxy@1.0.0 --pluggedin-api-key YOUR_API_KEY
Configuration for MCP Clients
Claude Desktop
Add the following to your Claude Desktop configuration:
{
"mcpServers": {
"pluggedin": {
"command": "npx",
"args": ["-y", "@pluggedin/pluggedin-mcp-proxy@latest"],
"env": {
"PLUGGEDIN_API_KEY": "YOUR_API_KEY"
}
}
}
}
Cline
Add the following to your Cline configuration:
{
"mcpServers": {
"pluggedin": {
"command": "npx",
"args": ["-y", "@pluggedin/pluggedin-mcp-proxy@latest"],
"env": {
"PLUGGEDIN_API_KEY": "YOUR_API_KEY"
}
}
}
}
Cursor
For Cursor, you can use command-line arguments instead of environment variables:
npx -y @pluggedin/pluggedin-mcp-proxy@latest --pluggedin-api-key YOUR_API_KEY
⚙️ Configuration Options
Environment Variables
| Variable | Description | Required | Default |
|---|---|---|---|
PLUGGEDIN_API_KEY |
API key from plugged.in App | Yes | - |
PLUGGEDIN_API_BASE_URL |
Base URL for plugged.in App | No | https://plugged.in |
Command Line Arguments
Command line arguments take precedence over environment variables:
npx -y @pluggedin/pluggedin-mcp-proxy@latest --pluggedin-api-key YOUR_API_KEY --pluggedin-api-base-url https://your-custom-url.com
Transport Options
| Option | Description | Default |
|---|---|---|
--transport <type> |
Transport type: stdio or streamable-http |
stdio |
--port <number> |
Port for Streamable HTTP server | 12006 |
--stateless |
Enable stateless mode for Streamable HTTP | false |
--require-api-auth |
Require API key for Streamable HTTP requests | false |
For a complete list of options:
npx -y @pluggedin/pluggedin-mcp-proxy@latest --help
🌐 Streamable HTTP Mode
The proxy can run as an HTTP server instead of STDIO, enabling web-based access and remote connections.
Basic Usage
# Run as HTTP server on default port (12006)
npx -y @pluggedin/pluggedin-mcp-proxy@latest --transport streamable-http --pluggedin-api-key YOUR_API_KEY
# Custom port
npx -y @pluggedin/pluggedin-mcp-proxy@latest --transport streamable-http --port 8080 --pluggedin-api-key YOUR_API_KEY
# With authentication required
npx -y @pluggedin/pluggedin-mcp-proxy@latest --transport streamable-http --require-api-auth --pluggedin-api-key YOUR_API_KEY
# Stateless mode (new session per request)
npx -y @pluggedin/pluggedin-mcp-proxy@latest --transport streamable-http --stateless --pluggedin-api-key YOUR_API_KEY
HTTP Endpoints
POST /mcp- Send MCP messagesGET /mcp- Server-sent events stream (optional)DELETE /mcp- Terminate sessionGET /health- Health check endpoint
Session Management
In stateful mode (default), use the mcp-session-id header to maintain sessions:
# First request creates a session
curl -X POST http://localhost:12006/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","method":"tools/list","id":1}'
# Subsequent requests use the same session
curl -X POST http://localhost:12006/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "mcp-session-id: YOUR_SESSION_ID" \
-d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"tool_name"},"id":2}'
Authentication
When using --require-api-auth, include your API key as a Bearer token:
curl -X POST http://localhost:12006/mcp \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","method":"ping","id":1}'
🐳 Docker Usage
You can also build and run the proxy server using Docker.
Building the Image
Ensure you have Docker installed and running. Navigate to the pluggedin-mcp directory and run:
docker build -t pluggedin-mcp-proxy:latest .
A .dockerignore file is included to optimize the build context.
Running the Container
STDIO Mode (Default)
Run the container in STDIO mode for MCP Inspector testing:
docker run -it --rm \
-e PLUGGEDIN_API_KEY="YOUR_API_KEY" \
-e PLUGGEDIN_API_BASE_URL="YOUR_API_BASE_URL" \
--name pluggedin-mcp-container \
pluggedin-mcp-proxy:latest
Streamable HTTP Mode
Run the container as an HTTP server:
docker run -d --rm \
-e PLUGGEDIN_API_KEY="YOUR_API_KEY" \
-e PLUGGEDIN_API_BASE_URL="YOUR_API_BASE_URL" \
-p 12006:12006 \
--name pluggedin-mcp-http \
pluggedin-mcp-proxy:latest \
--transport streamable-http --port 12006
Replace YOUR_API_KEY and YOUR_API_BASE_URL (if not using the default https://plugged.in).
Testing with MCP Inspector
While the container is running, you can connect to it using the MCP Inspector:
npx @modelcontextprotocol/inspector docker://pluggedin-mcp-container
This will connect to the standard input/output of the running container.
Stopping the Container
Press Ctrl+C in the terminal where docker run is executing. The --rm flag ensures the container is removed automatically upon stopping.
🏗️ System Architecture
The plugged.in MCP Proxy Server acts as a bridge between MCP clients and multiple underlying MCP servers:
🔄 Workflow
- Configuration: The proxy fetches server configurations from the plugged.in App
- Smart Discovery (
pluggedin_discover_tools):- Cache Check: First checks for existing cached data (< 1 second)
- Instant Response: Returns static tools + cached dynamic tools immediately
- Background Refresh: For
force_refresh=true, runs discovery in background while showing current tools - Fresh Discovery: Only runs full discovery if no cached data exists
- Capability Listing: The proxy fetches discovered capabilities from plugged.in App APIs
tools/list: Fetches from/api/tools(includes static + dynamic tools)resources/list: Fetches from/api/resourcesresource-templates/list: Fetches from/api/resource-templatesprompts/list: Fetches from/api/promptsand/api/custom-instructions, merges results
- Capability Resolution: The proxy resolves capabilities to target servers
tools/call: Parses prefix from tool name, looks up server in internal mapresources/read: Calls/api/resolve/resource?uri=...to get server detailsprompts/get: Checks for custom instruction prefix or calls/api/resolve/prompt?name=...
- Request Routing: Requests are routed to the appropriate underlying MCP server
- Response Handling: Responses from the underlying servers are returned to the client
🔒 Security Features
The plugged.in MCP Proxy implements comprehensive security measures to protect your system and data:
Input Validation & Sanitization
- Command Injection Prevention: All commands and arguments are validated against allowlists before execution
- Environment Variable Security: Secure parsing of
.envfiles with proper handling of quotes and multiline values - Token Validation: Strong regex patterns for API keys and authentication tokens (32-64 hex characters)
Network Security
- SSRF Protection: URL validation blocks access to:
- Localhost and loopback addresses (127.0.0.1, ::1)
- Private IP ranges (10.x, 172.16-31.x, 192.168.x)
- Link-local addresses (169.254.x)
- Multicast and reserved ranges
- Common internal service ports (SSH, databases, etc.)
- Header Validation: Protection against header injection with:
- Dangerous header blocking
- RFC 7230 compliant header name validation
- Control character detection
- Header size limits (8KB max)
- Rate Limiting:
- Tool calls: 60 requests per minute
- API calls: 100 requests per minute
- Error Sanitization: Prevents information disclosure by sanitizing error messages
Process Security
- Safe Command Execution: Uses
execFile()instead ofexec()to prevent shell injection - Command Allowlist: Only permits execution of:
node,npx- Node.js commandspython,python3- Python commandsuv,uvx,uvenv- UV Python tools
- Argument Sanitization: Removes shell metacharacters and control characters from all arguments
- Environment Variable Validation: Only allows alphanumeric keys with underscores
Streamable HTTP Security
- Lazy Authentication: Tool discovery doesn't require authentication, improving compatibility
- Session Security: Cryptographically secure session ID generation
- CORS Protection: Configurable CORS headers for web access
- Request Size Limits: Prevents DoS through large payloads
Security Utilities
A dedicated security-utils.ts module provides:
- Bearer token validation
- URL validation with SSRF protection
- Command argument sanitization
- Environment variable validation
- Rate limiting implementation
- Error message sanitization
For detailed security implementation, see SECURITY.md.
🧩 Integration with plugged.in App
The plugged.in MCP Proxy Server is designed to work seamlessly with the plugged.in App, which provides:
- A web-based interface for managing MCP server configurations
- Centralized capability discovery (Tools, Resources, Templates, Prompts)
- RAG v2 Document Library: Upload documents and enable AI-generated content with full attribution
- Custom instructions management
- Multi-workspace support for different configuration sets
- An interactive playground for testing MCP tools with any AI model
- User authentication and API key management
- AI Document Exchange: Create, search, and manage documents with model attribution tracking
📚 Related Resources
- plugged.in App Repository
- Model Context Protocol (MCP) Specification
- Claude Desktop Documentation
- Cline Documentation
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📝 Recent Updates
Version 1.5.0 (January 2025) - RAG v2
🤖 AI Document Exchange
- AI-Generated Documents: MCP servers can now create documents in your library with full AI attribution
- Model Attribution Tracking: Complete history of which AI models created or updated each document
- Advanced Document Search: Filter by AI model, provider, date, tags, and source type
- Document Versioning: Track changes and maintain version history for AI-generated content
- Multi-Source Support: Documents from uploads, AI generation, or API integrations
🔍 Enhanced RAG Capabilities
- Semantic Search: Improved relevance scoring with PostgreSQL full-text search
- Smart Filtering: Filter results by visibility, model attribution, and document source
- Snippet Generation: Automatic snippet extraction with keyword highlighting
- Performance Optimization: Faster queries with optimized indexing
Version 1.2.0 (January 2025)
🔒 Security Enhancements
- URL Validation: Comprehensive SSRF protection blocking private IPs, localhost, and dangerous ports
- Command Allowlisting: Only approved commands (node, npx, python, etc.) can be executed
- Header Sanitization: Protection against header injection attacks
- Lazy Authentication: Improved Smithery compatibility with auth-free tool discovery
🚀 Performance Improvements
- Optimized Docker Builds: Multi-stage builds for minimal container footprint
- Production Dependencies Only: Test files and dev dependencies excluded from Docker images
- Resource Efficiency: Designed for deployment in resource-constrained environments
🔧 Technical Improvements
- Enhanced error handling in Streamable HTTP transport
- Better session cleanup and memory management
- Improved TypeScript types and code organization
Version 1.1.0 (December 2024)
🚀 New Features
- Streamable HTTP Support: Connect to downstream MCP servers using the modern Streamable HTTP transport
- HTTP Server Mode: Run the proxy as an HTTP server for web-based access
- Flexible Session Management: Choose between stateless or stateful modes
- Authentication Options: Optional Bearer token authentication for HTTP endpoints
- Health Monitoring:
/healthendpoint for service monitoring
🔧 Technical Improvements
- Updated MCP SDK to v1.13.1 for latest protocol support
- Added Express.js integration for HTTP server functionality
- Enhanced TypeScript types for better developer experience
Version 1.0.0 (June 2025)
🎯 Major Features
- Real-Time Notification System: Track all MCP activities with comprehensive notification support
- RAG Integration: Support for document-enhanced queries through the plugged.in App
- Inspector Scripts: New automated testing tools for debugging and development
- Health Monitoring: Built-in ping endpoint for connection monitoring
🔒 Security Enhancements
- Input Validation: Industry-standard validation and sanitization for all inputs
- URL Security: Enhanced URL validation with SSRF protection
- Environment Security: Secure parsing of environment variables with dotenv
- Error Sanitization: Prevents information disclosure in error responses
🐛 Bug Fixes
- Fixed JSON-RPC protocol interference (stdout vs stderr separation)
- Resolved localhost URL validation for development environments
- Fixed API key handling in inspector scripts
- Improved connection stability and memory management
🔧 Developer Tools
- New inspector scripts for automated testing
- Improved error messages and debugging capabilities
- Structured logging with proper stderr usage
- Enhanced TypeScript type safety
See Release Notes for complete details.
🧪 Testing and Development
Local Development
Tests are included for development purposes but are excluded from Docker builds to minimize the container footprint.
# Run tests locally
npm test
# or
./scripts/test-local.sh
# Run tests in watch mode
npm run test:watch
# Run tests with UI
npm run test:ui
Lightweight Docker Builds
The Docker image is optimized for minimal footprint:
- Multi-stage build process
- Only production dependencies in final image
- Test files and dev dependencies excluded
- Optimized for resource-constrained environments
# Build optimized Docker image
docker build -t pluggedin-mcp .
# Check image size
docker images pluggedin-mcp
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgements
- Inspired by the MCP Proxy Server
- Built on the Model Context Protocol
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Plugged.in MCP Proxy Server's Information
- Author
- VeriTeknik
- Category
- AI Services
- Language
- TypeScript
- License
- Apache License 2.0
- Version
- v1.8.2
- Stars
- 20
- Updated
- about 2 months ago
Configuration
{
"mcpServers": {
"pluggedin": {
"command": "npx",
"args": [
"-y",
"@pluggedin/pluggedin-mcp-proxy@latest"
],
"env": {
"PLUGGEDIN_API_KEY": "<YOUR_API_KEY>"
}
}
}
}Configure Clients
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