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Navox Agents

github.com/navox-labs/agents official repository

Orchestrates a team of 15 specialist AI agents to run a full software engineering sprint cycle (think, plan, build, review, test, ship, reflect) within Claude…

agentSource repositoryRepository checked daily
Agentery price verdictNo pricing observedsource repository
SourcePublic repositorylicence not verified
Billing model
Last checked28 Jul 2026pricing & liveness

What it does

The specific capability behind this listing, and where to get it.

Orchestrates a team of 15 specialist AI agents to run a full software engineering sprint cycle (think, plan, build, review, test, ship, reflect) within Claude Code

Natural language build prompts/feature requests via Claude Code plugin commands or Python CLI → Written code, specs, architecture designs, code reviews, QA tests, tagged releases, pull requests, and retrospective learnings
Claude CodePython CLIGitHubautonomy: agentic
Price status · observed daily

Source repository available · no commercial pricing observed.

No price does not imply the product is free. Any code-host platform pricing is excluded.

Is Navox Agents good value?

Price is straightforward; the useful comparison is capability, compatibility and operational cost.

Source repository

Source repository available · no commercial pricing observed.

A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.

Observed commercial pricenone
NicheAutonomous Code Generation
Price benchmarknot applicable
What to compare instead

Check capability before deciding

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Comparable Autonomous Code Generation

Alternatives in the same niche, with observed price and liveness where available.

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See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
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  "agent_id": "navox_agents",
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  "logo": "https://agentery.com/logos/CP-BB2DKJ-128.png",
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  "category": "developer-tools-infra",
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  "task_performed": "Orchestrates a team of 15 specialist AI agents to run a full software engineering sprint cycle (think, plan, build, review, test, ship, reflect) within Claude Code",
  "inputs_accepted": [
    "Natural language build prompts/feature requests via Claude Code plugin commands or Python CLI"
  ],
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    "architecture designs",
    "code reviews",
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  ],
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  "protocols_or_interfaces": [],
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    "developer tools"
  ],
  "autonomy_level": "agentic",
  "human_approval_needed": "sometimes required",
  "pricing_model": "free",
  "price": {
    "observed": false,
    "billing": "not_found",
    "currency": null,
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": null,
    "summary": null,
    "confidence": "high",
    "source_url": "https://github.com/pricing",
    "checked_at": "2026-07-26T08:54:39.930Z",
    "amount": null,
    "display": null,
    "plans": [],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "MIT license",
    "13 GitHub stars",
    "case studies (crab cookie clicker, PipeWar game)",
    "built with Anthropic best practices"
  ],
  "evidence_quality": "high",
  "entity_type": "agent",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://github.com/navox-labs/agents"
  ],
  "last_checked": "2026-06-16",
  "how_to_connect": {
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    "docs": "https://github.com/documentation",
    "mcp": {
      "endpoint": "https://github.com/mcp.json",
      "transport": "http",
      "config_snippet": "{\n  \"mcpServers\": {\n    \"navox_agents\": {\n      \"url\": \"https://github.com/mcp.json\"\n    }\n  }\n}"
    },
    "a2a": null,
    "api": {
      "docs_url": "https://github.com/developer",
      "endpoint": null
    },
    "protocols": []
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 2293,
    "uptime_7d": 1,
    "checked_at": "2026-07-28T02:36:29.167Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}