English Français العربية

gutsy

السجل الرسمي الذكاء الاصطناعي والوكلاء

Local gut check before risky agent actions: calibrated safe/intended probabilities, no API calls.

الشيفرة المصدرية التوثيق

التثبيت

أضف هذا إلى إعدادات MCP في عميلك (Claude Desktop: claude_desktop_config.json، وCursor: ‏.cursor/mcp.json، ويستخدم VS Code وغيره الصيغة نفسها «mcpServers»).

PYPI package gutsy-mcp
Claude Code 
claude mcp add gutsy -e 'GUTSY_URL=http://127.0.0.1:8765' -e 'GUTSY_INFERENCE_DIR=<GUTSY_INFERENCE_DIR>' -e 'GUTSY_PROCEED_MIN=0.85' -e 'GUTSY_BLOCK_MIN=0.50' -- uvx gutsy-mcp==0.1.2
إعداد JSON (Claude Desktop وCursor وVS Code) 
{
    "mcpServers": {
        "gutsy": {
            "command": "uvx",
            "args": [
                "gutsy-mcp==0.1.2"
            ],
            "env": {
                "GUTSY_URL": "http://127.0.0.1:8765",
                "GUTSY_INFERENCE_DIR": "<GUTSY_INFERENCE_DIR>",
                "GUTSY_PROCEED_MIN": "0.85",
                "GUTSY_BLOCK_MIN": "0.50"
            }
        }
    }
}

متغيرات البيئة

  • GUTSY_URL URL of the local gutsy-inference server
  • GUTSY_INFERENCE_DIR Directory with models.json; if set, gutsy-mcp starts gutsy-inference itself
  • GUTSY_PROCEED_MIN Minimum P(proceed) and P(intended) to recommend proceeding
  • GUTSY_BLOCK_MIN Minimum P(block) to recommend blocking

التوثيق

مأخوذ من ملف README للمشروع على GitHub ويُحدَّث أسبوعيًا. تفتح الروابط على GitHub.

المحتويات
  1. gutsy-mcp
  2. What it is and isn't
  3. 1. Start the gutsy runtime
  4. 2. Add the MCP server
  5. 3. Optional: enforce it with a Claude Code hook
  6. Tool

gutsy-mcp

A local gut check for coding agents. Before Claude Code, Codex, Cursor or Copilot runs rm -rf, force-pushes, deploys or sends something, it calls gut_check and gets back calibrated probabilities that the action is intended and safe, plus a recommendation: proceed, confirm (ask the user first) or block.

Runs on your CPU with gutsy (0.8B, 775 MB GGUF). No API calls, no per-call cost, deterministic, and your code never leaves the machine.

What it is and isn't

It's a fast second opinion that adds friction where it's warranted. It is not a security boundary: the agent decides whether to call it and writes the context it sees, and a 0.8B model is weak at ambiguity and multi-step rules (see the model card). Keep your normal permission settings on. Default thresholds aren't tuned for your workflow; log the probabilities and adjust them.

1. Start the gutsy runtime

git clone https://github.com/kouhxp/gutsy
pip install -e gutsy/gutsy-inference
hf download kouhxp/gutsy --include "gutsy-0.8b-v04*" --local-dir gutsy/gutsy-inference/models
cd gutsy/gutsy-inference && cp models.example.json models.json
gutsy-inference check && gutsy-inference serve     # http://127.0.0.1:8765

Or set GUTSY_INFERENCE_DIR=/path/to/gutsy/gutsy-inference and gutsy-mcp starts it on first use.

2. Add the MCP server

Claude Code:

claude mcp add gutsy -- uvx gutsy-mcp

Cursor (.cursor/mcp.json) / Claude Desktop:

{ "mcpServers": { "gutsy": { "command": "uvx", "args": ["gutsy-mcp"] } } }

VS Code (.vscode/mcp.json):

{ "servers": { "gutsy": { "type": "stdio", "command": "uvx", "args": ["gutsy-mcp"] } } }

Codex (~/.codex/config.toml):

[mcp_servers.gutsy]
command = "uvx"
args = ["gutsy-mcp"]

Then tell the agent when to use it (CLAUDE.md, AGENTS.md, .cursor/rules):

Before deleting files, rewriting git history, force-pushing, touching databases, deploying, publishing or sending anything, call gut_check. If it doesn't return proceed, stop and ask me.

3. Optional: enforce it with a Claude Code hook

An MCP tool only runs if the agent remembers to call it. The hook runs on every risky-looking Bash command regardless. It can only ask or deny, never auto-approve.

uv tool install gutsy-mcp      # puts gutsy-hook on PATH

.claude/settings.json:

{
  "hooks": {
    "PreToolUse": [
      { "matcher": "Bash", "hooks": [{ "type": "command", "command": "gutsy-hook", "timeout": 60 }] }
    ]
  }
}

block becomes a confirmation prompt by default; set GUTSY_HOOK_ALLOW_DENY=1 to deny outright.

Tool

gut_check(action, context="", user_request="") returns:

{
  "recommendation": "confirm",
  "reason": "Not confident enough to proceed without the user.",
  "p_intended": 0.41,
  "p_reversible": 0.08,
  "verdict_probabilities": {"proceed": 0.22, "confirm": 0.61, "block": 0.17},
  "reject": 0.04,
  "confidence": 0.42
}
env vardefault
GUTSY_URLhttp://127.0.0.1:8765runtime URL
GUTSY_INFERENCE_DIRlets gutsy-mcp start the runtime
GUTSY_MODELruntime defaultmodel name from models.json
GUTSY_PROCEED_MIN0.85
GUTSY_BLOCK_MIN0.50
GUTSY_API_KEYif you run serve --api-key-env

License: Apache 2.0.

الأسئلة الشائعة

ما هو gutsy؟

Local gut check before risky agent actions: calibrated safe/intended probabilities, no API calls.

كيف أثبّت gutsy؟

يعمل على جهازك. في Claude Code: claude mcp add gutsy -e 'GUTSY_URL=http://127.0.0.1:8765' -e 'GUTSY_INFERENCE_DIR=<GUTSY_INFERENCE_DIR>' -e 'GUTSY_PROCEED_MIN=0.85' -e 'GUTSY_BLOCK_MIN=0.50' -- uvx gutsy-mcp==0.1.2. وفي العملاء الآخرين، الصق إعداد JSON من هذه الصفحة في إعدادات MCP الخاصة بهم.

هل يحتاج gutsy إلى مفتاح API؟

لا يذكر إدراجه في السجل أي مفتاح أو سر إلزامي. قد تتطلب بعض الميزات حسابًا لدى الخدمة التي يتصل بها.

هل gutsy مفتوح المصدر؟

نعم. شيفرته متاحة على GitHub بترخيص Apache-2.0.

من يصون gutsy؟

ينشره kouhxp. يدرجه AI.tn لكنه لا يصونه ولا يوصي به.

من سجل MCP الرسمي. الإدراج ليس توصية: راجع شيفرة الخادم وصلاحياته قبل منحه الوصول إلى بياناتك.