02 Quick Start

02 — Quick Start

Updated: 2026-09-29

After installation, this page walks through the first 30 minutes of using Nokido.

🚦 Verify the hub is up

curl http://localhost:8766/health
# {"status":"ok","version":"18.3","ts":"..."}

If you get Connection refused :

• Docker : docker compose -f docker/nokido/docker-compose.yml ps
• Native : nokido-hub (or python -m tools.nokido_hub)
• Windows NSSM : nssm status LaForge-Master

🔑 Configure your first LLM provider

Nokido stores API keys in a vault (DPAPI on Windows, Keychain on macOS, libsecret on Linux). Never in .env committed to git.

Open the web admin :

http://127.0.0.1:8766/admin/providers

You'll see the configured providers listed. Pick one (e.g. Groq — generous free tier) and click "🔑 Set key". Paste your API key, click "Save to vault". Done — Nokido will route to Groq when relevant.

CLI alternative :

nokido-vault set -k GROQ_API_KEY
# (paste key, hit enter)
nokido-secrets status     # verify

🎯 Your first call

import requests, json

# The hub refuses anonymous calls (401) : every call carries an agent's token and name
# (see 04 — MCP clients setup ; `tools/forge_mcp_json_sync.py --emit-headers <AGENT>`).
HEAD = {"Authorization": "Bearer <FORGE_TOKEN_...>", "X-Agent-Name": "CLAUDE",
        "Accept": "application/json, text/event-stream"}

resp = requests.post("http://localhost:8766/mcp", headers=HEAD, json={
    "jsonrpc": "2.0", "id": 1,
    "method": "tools/call",
    "params": {
        "name": "ask",
        "arguments": {
            "provider": "groq",     # or "auto" for cascade
            "message": "Explain the RAG pattern in 3 lines.",
        }
    }
}).json()

print(resp["result"]["content"][0]["text"])

The hub :

1. Picks groq from your vault key.
2. Routes via forge_llm_router.call_cascade (failover automatic).
3. Logs the call in network_log for telemetry.
4. Returns the answer.

🔌 Wire a CLI client

Nokido speaks MCP (Model Context Protocol). Pick your favorite client :

• Claude Desktop
• Claude Code
• Gemini CLI
• Codex CLI
• Cline (VS Code)

Or write a custom client : the Hub API reference documents the tools (read, run, query, rag, ask, orchestrate, etc.) — the exact list depends on your agent's ring (tools/list).

🧠 Use the local stack first

Nokido prioritizes local inference. Two ways to set it up :

Via Ollama (recommended for getting started)

# In the Docker compose
docker exec laforge-ollama ollama pull qwen2.5-coder:latest

# Or with native ollama
ollama pull qwen2.5-coder:latest

Then ask with provider="ollama_local".

Via llama.cpp (faster, more control)

llama-server on :8091 with qwen2.5-coder:7b-instruct-q4_K_M. See docs/llamacpp_setup.md. The supervised service NokidoLlamaNative is disabled by default (disabled = true in proxy_deno/core/services.toml) : enable it when you want this path.

🎨 Try the TUI

python tools/nokido_tui.py

(nokido-cli is the plain terminal client, not the TUI.)

One pane per agent (Claude, Gemini, Codex, Cline, Master) plus toggleable views (RAG, services, tasks, health, events...). Keybindings :

• Tab — next pane
• Ctrl+B — broadcast
• Ctrl+K — toggle RAG pane
• Ctrl+U — filter unread
• F1 — help modal

Full reference : 09 — TUI reference.

📂 Workflow examples

Ask the RAG before the cloud

# Search first
resp = requests.post("http://localhost:8766/mcp", headers=HEAD, json={
    "method": "tools/call",
    "params": {"name": "rag", "arguments": {
        "action": "search", "topic": "BGE-M3 embedding", "limit": 5}}
}).json()

# Then ask (provider="auto" includes RAG context if rag_context=True)
resp2 = requests.post("http://localhost:8766/mcp", headers=HEAD, json={
    "method": "tools/call",
    "params": {"name": "ask", "arguments": {
        "provider": "auto", "message": "How does BGE-M3 differ from sentence-bert?",
        "rag_context": True}}
}).json()

Deport a long task to a daemon

# Admin route : it takes an ADMIN bearer (anything else -> 401)
ADMIN = {"Authorization": "Bearer <admin token>"}

# Submit job, get id back -- the script must live under the repo (or C:/tmp)
resp = requests.post("http://localhost:8766/admin/run_job", headers=ADMIN, json={
    "script": "tools/forge_humaneval_runner.py",
    "script_args": "--provider mistral --max 164",
    "online": True,          # cloud provider -> network needed
    "lane": "bench",         # anti-saturation lane
}).json()
job_id = resp["job_id"]      # "etat": "ACCEPTED" -- accepted is not produced

# Poll status (the real state, reconciled)
status = requests.get(f"http://localhost:8766/admin/job/{job_id}", headers=ADMIN).json()

You don't have to wait for the result in your interactive session.

Use orchestrate for multi-step reasoning

resp = requests.post("http://localhost:8766/mcp", headers=HEAD, json={
    "method": "tools/call",
    "params": {"name": "orchestrate", "arguments": {
        "task": "Find all forge_*.py modules with cyclomatic complexity > 10, "
                "list them sorted by complexity, propose refactor for top 3.",
        "max_iter": 6,
    }}
}).json()

The hub orchestrates the LLM loop server-side. Your client doesn't carry the chain-of-thought in context.

⚠️ Common pitfalls

• Unauthorized — your client is missing Authorization: Bearer <token>
  • X-Agent-Name: <agent>. See 04 — MCP clients setup.
• ring 2 > max 0 — you tried query (raw SQL) which requires ring 0. Use rag (semantic search) instead. It's rule #1.
• Empty response — the provider's key is missing or quota exhausted. Check /admin/providers for the offending provider.

🚀 Next steps

• Tune cascade priorities in app/forge_provider_specs.py.
• Add custom tools via tools/forge_*.py (see CONTRIBUTING).
• Read the Manifesto for the why behind Nokido.
• Configure a second client to see multi-agent orchestration (Claude + Gemini).