AI API providers

A guide circulating among Linux users explains how to query and compare several large language models, including Claude, ChatGPT, DeepSeek, Grok and GLM, from the command line using Python and API aggregators. It walks through setting up access to multiple providers so outputs can be reviewed side by side, aimed at developers choosing between AI services or testing models on their own machines.

A developer is warning that OpenCode's model whitelist is effectively a list of promises made by other people's APIs, and that the list is slowly rotting as providers change or drop endpoints. A small tool called ocprobe has been introduced to check which models still actually work, highlighting how fragile dependency on third-party APIs can be for open-source coding tools.

Developers are debating OpenRouter's pricing model, noting the service charges a 5.5% fee when users add credits rather than a per-token markup on API calls. A breakdown compares the total cost of routing AI requests through OpenRouter versus paying providers directly or self-hosting an open-source proxy like LiteLLM, offering a decision rule for choosing between the three approaches.

Model Context Protocol, or MCP, is being framed as the standard that lets AI agents plug into a company's APIs and tools. But commentary from The New Stack stresses that the protocol only provides access — it does not govern what an agent should or should not see once connected. That means questions of permissions, filtering and data exposure still fall on developers and platform owners rather than on MCP itself.