Agent skill · Backend & API

add-atomic-chat-tool

Add Atomic Chat MCP server so the container agent can call local models served by the Atomic Chat desktop app via its OpenAI-compatible API.

NanoCo30,389★ · +78/wk · 1 repos on radarProfile →
claude-codeships scriptsMIT
Install
npx skills add nanocoai/nanoclaw --skill add-atomic-chat-tool --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 6
SKILL.md size: 10 KB
Bundled scripts: yes
Path: .claude/skills/add-atomic-chat-tool/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 30,426 · +37 this week
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Add Atomic Chat Integration This skill adds a stdio-based MCP server that exposes models running in the local [Atomic Chat](https://github.com/AtomicBot-ai/Atomic-Chat) desktop app as tools for the container agent. Claude remains the orchestrator but can offload work to local models served by Atomic Chat on `http://127.0.0.1:1337/v1` (OpenAI-compatible). Tools exposed: - `atomic_chat_list_models` — list models currently available in Atomic Chat (`GET /v1/models`) - `atomic_chat_generate` — send a prompt to a specified model and return the response (`POST /v1/chat/completions`) Model management (download, delete) is done through the **Atomic Chat desktop UI** — the app is a fork of Jan and manages its own model library. The skill ships the MCP server source (and its test) in this folder and copies them into the agent-runner tree at install time, then registers the server in `index.ts` and forwards host env vars in `container-runner.ts`. Registering the server is enough to expose its tools — the agent's allow-pattern (`mcp__atomic_chat__*`) is derived from the registered server name. ## Phase 1: Pre-flight ### Check if already applied Check if `container/agent-runner/src/atomic-cha

What's inside
Steps it walks through
  1. Phase 1: Pre-flight
  2. Check if already applied
  3. Check prerequisites
  4. Phase 2: Apply Code Changes
  5. Copy the skill's source and tests into both trees
  6. Register the MCP server in the agent-runner
  7. Forward host env vars into the container
  8. Surface [ATOMIC] log lines at info level
  9. Add env-var stubs to .env.example
  10. Validate code changes
  11. Phase 3: Configure
  12. Set Atomic Chat host (optional)
  13. Set API key (optional)
  14. Restart the service
Ships with 5 files
  • REMOVE.md
  • atomic-chat-env.ts
  • atomic-chat-mcp-stdio.ts
  • atomic-chat-registration.test.ts
  • atomic-chat-wiring.test.ts
Commands it runs
curl -s http://127.0.0.1:1337/v1/models | head
Container (Bun) tree — the MCP server and the registration wiring test
cp $S/atomic-chat-mcp-stdio.ts        container/agent-runner/src/atomic-chat-mcp-stdio.ts
cp $S/atomic-chat-registration.test.ts container/agent-runner/src/atomic-chat-registration.test.ts
Host (Node) tree — the env-forwarding helper and the wiring test
cp $S/atomic-chat-env.ts              src/atomic-chat-env.ts
cp $S/atomic-chat-wiring.test.ts      src/atomic-chat-wiring.test.ts
Atomic Chat MCP tool (.claude/skills/add-atomic-chat-tool)
Override the host where Atomic Chat exposes its OpenAI-compatible API.
Optional API key. Leave unset for a local Atomic Chat install — it does not require auth.
More from nanoclaw
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About this skill
What does the add-atomic-chat-tool skill do?

Add Atomic Chat MCP server so the container agent can call local models served by the Atomic Chat desktop app via its OpenAI-compatible API.

How do I install it?

Run `npx skills add nanocoai/nanoclaw --skill add-atomic-chat-tool --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From nanocoai/nanoclaw, a repository with 30,426 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going