Merge Gateway

Merge is a connective infrastructure platform and universal context engine for AI agents, developed for companies building internal and customer-facing AI products. It connects agents to company data, tools, and models, with capabilities for authenticated tool access, LLM routing, customer-data synchronization, workforce access control, shared skills, and security auditing. Its context-layer approach combines synchronized copies of large datasets with live API lookups. A router selects between cached or live context, a summarizer derives higher-level context, and company skills and memory encode organizational definitions and procedures. The system also tracks data provenance, including where context came from and when it may become invalid.

Merge Agent Handler is a tool-calling platform from Merge that provides production-ready MCP connectors for AI agents. It connects agents to thousands of third-party enterprise tools, with maintained connectors, guided user authentication, scoped access by agent type or environment, and controls for data governance, security alerts, and interaction logs. The connectors let agents perform actions such as sending messages, creating tickets, and running background tasks. Agent Handler is designed for internal and customer-facing applications and supports agent access to live tool connections while managing and monitoring tool interactions.

Vercel AI Gateway is a managed service from Vercel that routes application requests to language-model providers, centralizes API key management, and provides observability, caching, and rate-limiting for LLM usage. It is intended to simplify integration of multiple LLMs and enforce access controls for apps and autonomous agents.

LiteLLM is an open-source AI gateway and Python SDK from BerriAI for calling more than 100 LLM providers through a unified OpenAI-compatible interface. It supports direct library integration and a self-hosted proxy server, with provider-specific formats translated into common endpoints such as chat completions, responses, embeddings, image generation, audio, batches, reranking, messages, and agent-to-agent calls. The proxy provides centralized authentication and authorization, virtual keys, per-project and per-user spend tracking, logging, guardrails, caching, load balancing, routing with retry and fallback logic, and an administration dashboard. LiteLLM also exposes MCP tools and A2A agents through the gateway and can be deployed as a componentized stack with separate gateway, backend, and UI services. The repository describes it as open source and documents Docker, local development, and Terraform deployment options for AWS and Google Cloud.

FreeLLMAPI is an open-source proxy that aggregates free tiers from multiple LLM providers behind a single OpenAI-compatible `/v1` endpoint. It can also connect custom OpenAI-compatible chat, embedding, image, and audio endpoints, including local servers and remote gateways. Its router selects an available model, fails over when a provider is rate-limited, stores provider keys encrypted, and tracks per-key usage against free-tier limits. The router refreshes its model catalog from a signed feed; free installations receive periodic snapshots, while the hosted premium offering provides the live catalog. The project is intended for personal experimentation and is available as a self-hosted install with a hosted service at freellmapi.co.