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An open-source, local, read-only MCP server that checks your request before Google quietly hands back nothing Ask the Google Search Console API for clicks filtered by country us and you get zero rows. No error, no warning, just nothing. It's not the only one.
Meet Cline Desktop, an open-source app for open-weight models. Run parallel AI agents, automate recurring tasks, choose from 300+ models, and extend your workflow with plugins, MCP servers, and skills.
How Cline migrated its VS Code extension for 11 million developers to the new Cline SDK, built a safe A/B rollout, and reduced agent failures by 10x.
Benchmarking eight AI models on IMO 2026 problems in Cline, we found DeepSeek V4 Flash scored 30/42, clearing the gold medal cutoff for just $0.12. See how open-weight models compare with GPT-5.6 Sol, Claude Fable 5, Kimi K3, and more.
Build a code review agent with the Cline SDK using custom tools, guardrails, hooks, and a two-pass review workflow. Learn how to inspect PR diffs, filter false positives, audit tool usage, and post high-signal review comments to GitHub.
Learn how Cline evaluates and improves open weight coding agents using Terminal Bench, with practical heuristics for model performance, token efficiency, reasoning, providers, and eval optimization.
NVIDIA Nemotron 3.5 Lightning is now available in Cline, bringing a 30B MoE model with 3B active parameters, up to 1M context, and high throughput for agentic coding workflows.
Explore the best open weight models for coding in 2026. Compare Kimi K3, GLM 5.2, DeepSeek V4 Pro and Flash, and MiniMax M3 across benchmarks, pricing, model size, and developer use cases.
See how recursive self-improvement helped Cline optimize Kimi K3 and achieve an 88.8% SOTA score on Terminal-Bench 2.1 at a fraction of the cost.
A practical guide to the economics of self-hosting open-weight LLMs. Using Kimi K2.6 and real production traffic from Cline, this post breaks down GPU memory, inference, batching, pricing, and the point at which self-hosting can save millions.
ClinePass is a low-cost monthly subscription that pairs Cline's agent harness with a curated set of open-weight models and 2-5x the standard API rate limits, across every surface Cline runs on.
Learn how to extend the Cline agent loop with plugins and hooks to add custom behavior, lifecycle logging, and enforceable guardrails without rebuilding the harness.
Before “agents” became a buzzword, Cline was the first real agentic coding experience. Cline started with the VSCode extension and helped a generation of developers step into AI coding. It was a great VS Code extension, but as the technology evolves, it also taught us something uncomfortable: the
An engineer at Cline told me he was vibe coding on a road trip from his phone. His Mac was at home running Cline agents; he was checking on them from the passenger seat. Here's the setup.What you needYour phone and your Mac both need Tailscale
We built an arena where three AI coding agents fight to the death. Each agent runs on different hardware, a different inference stack, and a different economic model. They all receive the same task: write a bash script that kills your opponents, then execute it immediately. The last process standing
You're building on infrastructure you don't control, can't audit, and can't see degrading in real time.The Invisible DependencyFor engineers, the inference vendor problem starts with a deceptively simple question: what happens when the model changes and you don't
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