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Llmgateway MCP Server

Developer ToolsLow Risk10.0MCP RegistryRemote
Free

Server data from the Official MCP Registry

Chat with any LLM, generate images, browse models and check your usage and costs.

About

Chat with any LLM, generate images, browse models and check your usage and costs.

Remote endpoints: streamable-http: https://api.llmgateway.io/mcp

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

Endpoint verified · Requires authentication · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Found in Source Code

Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.

file_system

Applies to the server that hosts this plugin, not to your machine.

env_vars

Applies to the server that hosts this plugin, not to your machine.

database

Applies to the server that hosts this plugin, not to your machine.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-theopenco-llmgateway": {
      "url": "https://api.llmgateway.io/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

LLM Gateway

LLM Gateway is an open-source API gateway for Large Language Models (LLMs). It acts as a middleware between your applications and various LLM providers, allowing you to:

  • Route requests to multiple LLM providers (OpenAI, Anthropic, Google Vertex AI, and others)
  • Manage API keys for different providers in one place
  • Track token usage and costs across all your LLM interactions
  • Analyze performance metrics to optimize your LLM usage

Features

  • Unified API Interface: Compatible with the OpenAI API format for seamless migration
  • Usage Analytics: Track requests, tokens used, response times, and costs
  • Multi-provider Support: Connect to various LLM providers through a single gateway
  • Performance Monitoring: Compare different models' performance and cost-effectiveness

Getting Started

You can use LLM Gateway in two ways:

  • Hosted Version: For immediate use without setup, visit llmgateway.io to create an account and get an API key.
  • Self-Hosted: Deploy LLM Gateway on your own infrastructure for complete control over your data and configuration.

Self-Hosted With Docker

Use Docker-managed volumes for the unified image. Do not bind-mount a host directory directly to /var/lib/postgresql/data, because PostgreSQL initialization inside the container needs to set permissions on that directory and that can fail depending on the host filesystem and ownership.

export LLM_GATEWAY_SECRET="$(openssl rand -base64 32 | tr -d '\n')"
export GATEWAY_API_KEY_HASH_SECRET="$(openssl rand -base64 32 | tr -d '\n')"
./scripts/run-unified-container.sh

If you prefer a one-off docker run, use named volumes instead of ~/some-host-dir:

docker volume create llmgateway_postgres
docker volume create llmgateway_redis

docker run -d \
  --name llmgateway \
  --restart unless-stopped \
  -p 3002:3002 \
  -p 3003:3003 \
  -p 3005:3005 \
  -p 3006:3006 \
  -p 3007:3007 \
  -p 4001:4001 \
  -p 4002:4002 \
  -v llmgateway_postgres:/var/lib/postgresql/data \
  -v llmgateway_redis:/var/lib/redis \
  -e AUTH_SECRET="$LLM_GATEWAY_SECRET" \
  -e GATEWAY_API_KEY_HASH_SECRET="$GATEWAY_API_KEY_HASH_SECRET" \
  ghcr.io/theopenco/llmgateway-unified:latest

Using LLM Gateway API

curl -X POST https://api.llmgateway.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $LLM_GATEWAY_API_KEY" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {"role": "user", "content": "Hello, how are you?"}
  ]
}'

Development Setup

  1. Install dependencies and set up the development environment:

    pnpm i && pnpm run setup
    

    This will install all dependencies, start Docker services, sync the database schema, and seed initial data.

    Note for WSL2 users: Ensure Docker Desktop is running with WSL integration enabled.

  2. Start development servers:

    pnpm dev
    
  3. Build for production:

    pnpm build
    

Folder Structure

  • apps/ui: Next.js dashboard frontend
  • apps/playground: Lounge — consumer AI chat app (Next.js)
  • apps/code: Next.js Dev Plans + coding tools landing & dashboard
  • apps/airside: Airside — self-serve provider portal (Next.js)
  • apps/api: Hono backend
  • apps/gateway: API gateway for routing LLM requests
  • apps/docs: Documentation site
  • ee/admin: Internal admin dashboard
  • packages/db: Drizzle ORM schema and migrations
  • packages/models: Model and provider definitions
  • packages/shared: Shared types and utilities

Adding a provider

We do not accept pull requests that add new providers. Inference providers onboard through Airside, our self-serve provider portal, where you register and manage your model listings.

License

LLMGateway is available under a dual license:

  • Open Source: Core functionality is licensed under AGPLv3 - see the LICENSE file for details.
  • Enterprise: Commercial features in the ee/ directory require an Enterprise license; multi-organization administration requires a white-label license. See ee/LICENSE for details.

Enterprise features include:

  • Advanced billing and subscription management
  • Full request and response payload retention (Retain All Data); other plans are metadata only
  • Custom provider key configurations
  • Team and organization management
  • Priority support
  • And more to be defined

For enterprise licensing, please contact us at contact@llmgateway.io

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