PSKit
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PSKitShow git status and recent changes"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
PSKit
Neural-safe PowerShell automation for AI agents
PSKit is a Model Context Protocol server that gives AI agents 38 PowerShell tools backed by a 5-tier neural safety pipeline. Every command passes through a KAN (Kolmogorov-Arnold Network) neural scorer before execution — catching dangerous patterns in under 1 millisecond.
Works on Windows, Linux, and macOS with any MCP-compatible client: Claude Desktop, Claude Code, Cursor, Windsurf, Continue.dev, and more.
Install
Recommended — no virtual environment needed
uvx pskit-mcpWith pip
pip install pskit-mcpWith HTTP transport (for shared/remote use)
pip install "pskit-mcp[http]"
pskit serve --http --port 8000Platform support
OS | Install PowerShell 7 | Notes |
Windows 10/11 | ships pre-installed or | full feature set |
Ubuntu / Debian | Microsoft apt repo → | ✅ |
Fedora / RHEL |
| ✅ |
Arch Linux |
| ✅ |
macOS |
| ✅ |
On Linux and macOS the system-info tools use native POSIX sources:
/proc/meminfo (Linux) or sysctl+vm_stat (macOS) for memory,
df for disks, ss -tlnp (Linux) or lsof (macOS) for open ports.
Package installer auto-detects apt, dnf, pacman, and brew alongside
pip, npm, cargo, and winget.
Quick Start
Claude Desktop
Add to %APPDATA%\Claude\claude_desktop_config.json (Windows),
~/Library/Application Support/Claude/claude_desktop_config.json (macOS),
or ~/.config/Claude/claude_desktop_config.json (Linux):
{
"mcpServers": {
"pskit": {
"command": "uvx",
"args": ["pskit-mcp"],
"env": {
"PSKIT_ALLOWED_ROOT": "/home/you/projects"
}
}
}
}Replace PSKIT_ALLOWED_ROOT with your project root:
C:\Your\Projects on Windows, /home/you/projects on Linux,
/Users/you/projects on macOS.
Claude Code
claude mcp add pskit -- uvx pskit-mcpVerify it works
pskit doctorPSKit Doctor
+---------------------------+------+------------------------------------------+
| PowerShell (pwsh) | OK | PowerShell 7.5.0 |
| git | OK | git version 2.47.1 |
| ripgrep (rg) | OK | ripgrep 14.1.0 -- fast search active |
| nvidia-smi | WARN | not found -- gpu_status returns error |
| Ollama | OK | running at localhost:11434 |
| Allowed root | OK | /home/you/projects/myapp (or C:\... on Windows) |
| KAN model | WARN | no trained weights -- heuristic active |
+---------------------------+------+------------------------------------------+What AI Agents Can Do
Once connected, an agent can autonomously work across your entire project:
# Map the project structure
find_files("*.py", max_results=50)
list_directory("src/")
# Read, search, and edit files precisely
read_file("src/auth.py")
search_code("TODO", include="*.py", context=3)
edit_file("src/auth.py",
old_text="def login(user):",
new_text="def login(user: str) -> bool:")
# Full git workflow
git_status() # branch, changes, ahead/behind
git_diff(staged=True)
git_commit("feat: add type hints to auth module")
git_push()
# Run builds and tests with structured results
result = build_project()
# { success: true, exit_code: 0, stdout: "...", duration_ms: 4821 }
result = test_project(filter_expr="test_auth")
# { success: true, passed: 12, failed: 0, skipped: 2, duration_ms: 1203 }
# System and network inspection
disk_usage() # { drive: "C", free_gb: 142.3, total_gb: 476.9 }
port_status("8080,11434,5432") # which services are listening
http_request("http://localhost:8000/health") # localhost only
# Check and install dependencies
which("rg") # { found: true, version: "14.1.0" }
install_package("requests", manager="pip")Safety Pipeline
Every command passes through 5 tiers before execution:
Command Input
|
v
+---------------------------------------------+
| Tier 1 . Result Cache |
| SHA-256 keyed . 30s TTL . 128 LRU entries |
| Read-only hits served instantly |
+--------------------+------------------------+
| miss
v
+---------------------------------------------+
| Tier 2 . KAN Neural Scorer |
| 24 features . Kolmogorov-Arnold Network |
| Sub-millisecond risk classification |
+--------------------+------------------------+
|
v
+---------------------------------------------+
| Tier 3 . Dangerous Command Blocklist |
| Hard-blocks: Format-Volume, rm -rf, |
| mass deletion, privilege escalation |
+--------------------+------------------------+
|
v
+---------------------------------------------+
| Tier 4 . Path Safety Check |
| Enforces PSKIT_ALLOWED_ROOT boundary |
| Blocks writes outside project root |
+--------------------+------------------------+
| elevated only
v
+---------------------------------------------+
| Tier 5 . Gemma LLM Review (optional) |
| Ollama-backed . Fail-open if offline |
| Deep semantic analysis of intent |
+--------------------+------------------------+
|
v
ExecuteKAN Neural Safety
PSKit uses a Kolmogorov-Arnold Network to score every command across 24 structural features before execution:
Feature Group | What It Detects |
Structure | command length, pipe depth, semicolons, nesting |
Dangerous patterns |
|
Network | outbound requests, drive mappings, mail |
Credentials |
|
Obfuscation | base64 encoding, variable expansion, string interpolation |
Persistence | registry writes, scheduled task creation, service installs |
Output | redirection, file output, compression |
Unlike rule-based filters, KAN learns non-linear risk combinations. Scores 0.0 (safe) to 1.0 (dangerous) in under 1ms, acting as an always-on pre-filter before the optional Ollama LLM review.
Built-In Agent Workflows
PSKit ships 6 ready-to-use MCP prompts accessible from Claude's prompt library:
Prompt | What It Does |
Audit Project | Full sweep: git state, structure, build, tests, system health |
Review Changes | Pre-commit diff review with commit message suggestion |
Diagnose Build | Systematic failure investigation with specific code fix |
Orient to Project | First-session orientation before starting any work |
Refactor File | Targeted single-file cleanup with stash safety net |
Write Tests For | Generate tests following existing project conventions |
Plus a pskit://guide resource Claude can read anytime for the complete tool reference, and a pskit://status resource for live server health.
Tools (38 total)
Category | Tools |
File |
|
Search |
|
Shell |
|
Environment |
|
Git |
|
System |
|
Network |
|
Build |
|
All 38 tools return typed structured output with auto-generated JSON schemas. Annotated with readOnly, destructive, and idempotent hints so clients auto-approve safe operations and warn on destructive ones.
CLI
pskit serve # Start MCP server on stdio (default)
pskit serve --http # Start on streamable HTTP (port 8000)
pskit doctor # System health check
pskit audit # View recent command audit log with KAN scores
pskit version # Print versionConfiguration
Variable | Default | Description |
| Current directory | File writes sandboxed to this path |
|
| Pre-warmed PowerShell session count |
|
| Ollama model for Tier 5 review |
|
| Ollama endpoint |
Or use pskit.config.toml in your project root:
[pskit]
allowed_root = "."
pool_size = 5
safety_model = "gemma3:4b"Audit Log
Every command is logged to .pskit/audit.jsonl with KAN score, safety verdict, and duration:
pskit auditPSKit Audit (last 50)
+---------------------+----------+-------+------+-------------------------------------+
| Time | Verdict | KAN | ms | Command |
+---------------------+----------+-------+------+-------------------------------------+
| 2026-04-06 15:42:11 | safe | 0.023 | 18 | Get-PSKitGitStatus |
| 2026-04-06 15:42:14 | safe | 0.031 | 247 | Read-PSKitFile 'src/auth.py' |
| 2026-04-06 15:42:19 | caution | 0.441 | 892 | Invoke-PSKitHttpRequest 'localhost' |
+---------------------+----------+-------+------+-------------------------------------+
Total: 47 Blocked: 0 Avg KAN: 0.089 Avg ms: 124Requirements
Python 3.11+
PowerShell 7.0+ —
pwshon PATH (download)PyTorch 2.0+ — for the KAN neural scorer
ripgrep (optional) — faster file search when
rgis on PATHOllama (optional) — enables Tier 5 Gemma LLM safety review
Powered by Loom
PSKit was extracted from Loom, a multi-agent orchestration platform. Loom uses PSKit as its PowerShell execution layer.
Contributing
git clone https://github.com/Nickalus12/pskit
pip install -e ".[dev]"
python -m pytest tests/ -q # 38 tests, no live PS session required
ruff check src/ # lintSee CLAUDE.md for architecture docs and the guide to adding new tools.
License
MIT (c) 2025-2026 Nickalus Brewer
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