Each provider has a default model; set <PROVIDER>_MODEL to pick another, or use /switch at runtime. Have a ChatGPT, Claude or Copilot plan? Skip the key and run /auth login <provider> inside ChatCLI. All fourteen providers are in Supported models.
3
Start chatting
chatcli
You are talking to an LLM in your terminal, with your project’s context one @ away. Next, try coder mode.
One prompt, real work: /coder runs the failing tests, reads the code, patches the bug and re-runs go test uncached to prove the fix — live, on Claude Sonnet 5.5
In practice, your everyday terminal turns into this:
$ chatcli› @git write the commit message from the staged diff ⮑ feat(api): add pagination to the /users endpoint› /agent fix the failing test in ./cli/plugins ⮑ plan: run tests → locate the failure → edit → re-verify ✓› @diagram gomod root=. output=~/arch.svg ⮑ Diagram rendered → ~/arch.svg (SVG, 245 KB)
On LongMemEval-S — 500 questions, each over about 115k tokens of past conversations — chatcli answered 90.8% by searching its own saved sessions, and 90.0% on the questions never used to tune it. Its search surfaced the evidence in 469 of 470 answerable questions.
See the full LongMemEval results
The method, every number, where it fails, what it changed in chatcli, and the data to rerun it.
ChatCLI brings the leading large language models (LLMs) straight into your shell. It understands your project’s context, edits code, runs commands and automates complex tasks, without you ever leaving the command line. A single Go binary: fast, portable and self-contained.
14 providers
OpenAI, Claude, Gemini, Grok, Ollama and more — in a single interface.
350+ models
One unified catalog. Switch model at any time.
37+ native tools
@coder, @lsp, @proc, @http, @api-explorer, @knowledge, @memory and many more.
The CLI is the main product — it works 100% locally, no server required. The server and operator are optional for team and Kubernetes scenarios. All versions are published automatically on every release via GitHub Actions. Check the full history on Releases or ArtifactHub.
Who is it for?
Developers: debug code, understand codebases, generate tests, refactor and document, all without leaving the terminal.
DevOps and SREs: analyze K8s logs, automate deploys, diagnose incidents with AI and monitor clusters.
CLI enthusiasts: supercharge your terminal, create powerful aliases and explore new ways to work with AI.
DBAs and data engineers: automate repetitive tasks, analyze queries, manage databases and data pipelines.
What does it replace?
Endless copy and paste: no more cat file.js, selecting, copying, opening the browser and pasting. Use @file right in the terminal.
Generic commits: @git plus a question gives a commit message based on the actual diff.
Intimidating log analysis: pipe straight to the AI with cat error.log | chatcli -p "root cause?".
A steep learning curve: @file ./src --mode smart and ask “how does auth work?”, and onboarding takes minutes.
ChatCLI ships as three artifacts that work standalone or together: the local CLI, the gRPC server, and the Kubernetes operator. Use just the CLI on your terminal, or set up a full topology with server + operator for teams and production environments.
1.223.0 — The binary you install and use in your terminal. Interactive mode, agent, coder, smart context, and remote server connection. brew install chatcli · go install · binary
gRPC server
1.223.0 — Centralized deployment for teams. Clients connect via chatcli connect and share LLM providers, sessions, and plugins. ghcr.io/diillson/chatcli:1.223.0
AIOps operator
1.223.0 — Autonomous incident detection, AI-powered analysis, and automated remediation for Kubernetes clusters. 17 CRDs, 54+ actions. ghcr.io/diillson/chatcli-operator:1.223.0
Helm charts
1.223.0 — Distributed via ArtifactHub and OCI registry on GHCR. oci://ghcr.io/diillson/charts/chatcli oci://ghcr.io/diillson/charts/chatcli-operator
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