Top SitesLLM Gateway - Unified API for Multiple LLM Providers

Machine Readiness

Stored receipt and evidence

Overall

30

Readable

100

Callable

0

Commerce

0

Payment

0

Machine Access

Inspect the site's MCP endpoint

Open MCP explorer

DialtoneApp can scan the stored discovery files for this domain, try the MCP initialize handshake, and show the raw protocol transcript.

Purchase boundary

read only

Control boundary

unknown

Payment rails

None

Payment providers

None

Payment methods

None

Payment protocols

None

Payment assets

None

Payment networks

None

Capabilities

None

Verified payment surface

No

Crypto only

No

Readable docs

robots, llms, llms-full

Products

0

Variants

0

Priced variants

0

Currencies

0

Offers

0

Priced offers

0

Priced actions

0

Samples

Offer samples

No stored offer samples.

Samples

Action samples

No stored action samples.

Samples

Product samples

No stored product samples.

Document

robots.txt

Open robots.txt
User-Agent: *
Allow: /
Disallow: /dashboard/
Disallow: /api/
Disallow: /onboarding

Sitemap: https://llmgateway.io/sitemap.xml

Document

llms.txt

Open llms.txt
# LLM Gateway Documentation

> Documentation for LLM Gateway - a full-stack LLM API gateway

## Docs

- [Introduction](/): LLM Gateway is an open-source API gateway for Large Language Models. Route requests to multiple providers, manage API keys, track usage, and optimize costs.
- [Overview](/overview): Introduction to LLM Gateway, an open-source API gateway for LLMs.
- [Quickstart](/quick-start): Fastest way to start using LLM Gateway in any language or framework.
- [Self Host LLMGateway](/self-host): Simple guide to self-hosting LLMGateway using Docker.
- [Health check](/health): LLM Gateway health check endpoint to verify the API is reachable and returning a 200 response.
- [Chat Completions](/v1_chat_completions): Create OpenAI-compatible chat completions through LLM Gateway. Route requests to any supported model across OpenAI, Anthropic, Google, and 20+ providers.
- [Anthropic Messages](/v1_messages): Send requests using the Anthropic Messages API format through LLM Gateway and route them to any supported provider with a unified interface.
- [Models](/v1_models): List all available AI models supported by LLM Gateway, including pricing, context window, and capability metadata for each provider.
- [Moderations](/v1_moderations): Classify text or multimodal inputs with OpenAI-compatible moderation through LLM Gateway to detect unsafe or policy-violating content.
- [Create Video](/v1_videos): Create an asynchronous video generation job through LLM Gateway using the OpenAI-compatible video API across supported providers.
- [Video Content](/v1_videos_content): Stream the generated video content from LLM Gateway once the asynchronous video generation job has completed successfully.
- [Retrieve Video](/v1_videos_retrieve): Retrieve the current state and metadata of an LLM Gateway video generation job, including progress, status, and output details.
- [Anthropic API Compatibility](/features/anthropic-endpoint): Use the Anthropic-compatible endpoint to access any LLM model through the familiar Anthropic API format.
- [API Keys & IAM Rules](/features/api-keys): Comprehensive guide to API key management and Identity Access Management (IAM) rules for fine-grained access control
- [Audit Logs](/features/audit-logs): Track all organization activity with comprehensive audit logs
- [Caching](/features/caching): Reduce costs and latency by caching identical requests.
- [Cost Breakdown](/features/cost-breakdown): Get real-time cost information for each API request directly in the response.
- [Custom Providers](/features/custom-providers): Learn how to integrate custom OpenAI-compatible providers with LLMGateway for enhanced flexibility and control.
- [Data Retention](/features/data-retention): Store and access your full request and response data for debugging, analytics, and compliance.
- [Guardrails](/features/guardrails): Protect your LLM usage with content guardrails that detect and block harmful content
- [Image Generation](/features/image-generation): Generate images using AI models through the OpenAI-compatible images API or chat completions API
- [Metadata](/features/metadata): Send additional context and metadata to LLM Gateway using custom headers.
- [Moderations](/features/moderations): Classify unsafe text and image inputs with the OpenAI-compatible moderations API
- [Reasoning](/features/reasoning): Learn how to use reasoning-capable models that show their step-by-step thought process.
- [Response Healing](/features/response-healing): Automatically repair malformed JSON responses from AI models.
- [Routing](/features/routing): Learn how LLMGateway intelligently routes your requests to the best available models and providers.
- [Source Attribution](/features/source): Use the X-Source header to identify your domain for public usage statistics.
- [Video Generation](/features/video-generation): Generate videos with an OpenAI-compatible async API and signed completion callbacks
- [Vision Support](/features/vision): Learn how to send images to vision-enabled models using URLs or inline base64 data.
- [Native Web Search](/features/web-search): Enable real-time web search capabilities to get up-to-date information from the internet.
- [Agent Skills](/guides/agent-skills): Packaged instructions and guidelines for AI coding agents
- [Autohand Code Integration](/guides/autohand): Use GPT-5, Claude, Gemini, or any model with Autohand Code's autonomous coding agent. Simple config, full cost tracking.
- [Claude Code Integration](/guides/claude-code): Use GPT-5, Gemini, or any model with Claude Code. Three environment variables, full cost tracking.
- [LLM Gateway CLI](/guides/cli): Command-line tool for scaffolding and managing LLM Gateway projects
- [Cline Integration](/guides/cline): Use LLM Gateway with Cline for AI-powered coding assistance in VS Code
- [Codex CLI Integration](/guides/codex-cli): Use any model with OpenAI's Codex CLI through LLM Gateway. One config file, full cost tracking.
- [Cursor Integration](/guides/cursor): Use LLM Gateway with Cursor IDE for AI-powered code editing and chat
- [Model Context Protocol (MCP)](/guides/mcp): Use LLM Gateway as an MCP server for Claude Code, Cursor, and other MCP-compatible clients
- [N8n Integration](/guides/n8n): Connect n8n workflow automation to LLM Gateway for AI-powered workflows
- [OpenClaw Integration](/guides/openclaw): Use GPT-5.4, Claude Opus, Gemini, or any model with OpenClaw across Discord, WhatsApp, Telegram, and more
- [OpenCode Integration](/guides/opencode): Connect OpenCode to 210+ models through LLM Gateway's built-in provider. No config files needed — just select, authenticate, and code.
- [AWS Bedrock Integration](/integrations/aws-bedrock): Connect AWS Bedrock to LLM Gateway for access to foundation models
- [Azure Integration](/integrations/azure): Connect Azure to LLM Gateway for enterprise-grade OpenAI models
- [Activity](/learn/activity): View and inspect every API request made through LLM Gateway
- [Agents](/learn/agents): Monitor your AI coding agents and their activity
- [API Keys](/learn/api-keys): Create, limit, and control API keys for authenticating with LLM Gateway
- [Audit Logs](/learn/audit-logs): Track every action taken within your organization
- [Billing](/learn/billing): Manage your credits, subscription plan, and payment methods
- [Dashboard](/learn/dashboard): Your central hub for monitoring LLM usage, costs, and performance
- [Guardrails](/learn/guardrails): Configure content safety rules to protect your LLM usage
- [Introduction](/learn): Learn how to navigate and use the LLM Gateway dashboard
- [Model Usage](/learn/model-usage): Track usage breakdown by individual model
- [Org Preferences](/learn/org-preferences): Manage your organization's name, billing email, and billing details
- [Group Chat](/learn/playground-group): Watch multiple AI models discuss and collaborate on your prompt
- [Image Studio](/learn/playground-image): Generate and edit images using AI models
- [Video Studio](/learn/playground-video): Generate videos using AI models
- [Chat Playground](/learn/playground): Test LLM models interactively with a full-featured chat interface
- [Policies](/learn/policies): Configure data retention and other organization policies
- [Preferences](/learn/preferences): Configure project-level settings including caching and project mode
- [Provider Keys](/learn/provider-keys): Bring your own provider API keys to use without additional fees
- [Referrals](/learn/referrals): Earn credits by referring other users to LLM Gateway
- [Security Events](/learn/security-events): Monitor guardrail violations and content policy events
- [Team](/learn/team): Manage team members and their roles within your organization
- [Transactions](/learn/transactions): View your complete payment and credit history
- [Usage & Metrics](/learn/usage-metrics): Detailed analytics for requests, models, errors, caching, and costs
- [Migrate from LiteLLM](/migrations/litellm): Switch from self-hosted LiteLLM to managed LLM Gateway. Same API format, zero infrastructure to maintain.
- [Migrate from OpenRouter](/migrations/openrouter): Switch to LLM Gateway for built-in analytics, self-hosting options, and simpler API. Two-line code change.
- [Migrate from Vercel AI Gateway](/migrations/vercel-ai-gateway): Keep your Vercel AI SDK code, add response caching, detailed analytics, and smart routing. One provider for all models.
- [Rate Limits](/resources/rate-limits): Understanding rate limits for free and paid models on LLMGateway.

Document

llms-full.txt

Not stored for this site.