sef-agents 3.12.0

SEF Agents — AI-powered guidance for the Synchronous Engineering Framework. Built on Model Context Protocol (MCP).

SEF Agents

AI-Powered Guidance for the Synchronous Engineering Framework

SEF Agents provides agent-based AI guidance, codebase mapping, and quality enforcement for the Synchronous Engineering Framework (SEF).

Built on Anthropic's Model Context Protocol (MCP) for universal AI assistant compatibility.

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Table of Contents

• What This Does
• Features
• Security
• Installation
• Configuration
• Local Development
• Quick Start
• Contributing
• About
• License

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What This Does

SEF Agents is an MCP server that connects to your AI assistant (Cursor, Claude Desktop, Windsurf). Once connected, it provides:

1. Agent-based prompts — Specialized guidance for 13 agents (10 SDLC + 3 utility)
2. Quality enforcement tools — Scan code for compliance, debt, security
3. Workflow orchestration — Track story state, dependencies, handoffs

Important: This is not a standalone app. It requires an MCP-compatible AI assistant.

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Features

Agent-Based Guidance (13 Agents)

SDLC Workflow Agents (10)

Agent	Function
discovery	Brownfield codebase scanning, CODE_MAP generation
product_manager	Requirements, acceptance criteria
qa_lead	Validates AC before development begins
architect	System design, boundaries, integration points
developer	Elite Code Quality Protocol enforcement
tester	Test standards, real-execution tests
pr_reviewer	PR review, AI anti-pattern detection
scrum_master	Process orchestration, handoff tracking
security_owner	Security audit, vulnerability scanning
test_designer	Conceptual test design, BDD architecture

Utility Agents (3) — On-Demand

Agent	Function
forensic_engineer	Incident investigation, 5 Whys, post-mortems
strategist	Solution brainstorming, trade-off analysis
platform_engineer	DevEx, health scanning, code quality enforcement

Quality Tools

Tool	What It Does
generate_codemap	Auto-document directory structure
validate_compliance	Check code against SEF standards
detect_ai_patterns	Find AI-generated code smells
scan_debt	Detect technical debt (TODOs, bare exceptions, etc.)
scan_external_dependencies	Find env vars, API clients, external URLs
scan_code_quality	AST-based pe_rules enforcement (bare except, types, logging)
scan_health	Unified health report across all quality dimensions

Workflow Tools

Tool	What It Does
init_workflow	Start tracking a story
get_workflow_state	See current phase, blockers, artifacts
suggest_next_agent	Auto-suggest agent transitions
generate_story_dependency_graph	Visualize story dependencies
detect_flow_gaps	Find broken E2E flows

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Security

SEF Agents is designed with security as a core principle:

• ✅ No Network Calls: Contains no HTTP clients, sockets, or external communication
• ✅ No Data Exfiltration: All operations are local-only
• ✅ No Hardcoded Secrets: Scanned for credentials and API keys
• ✅ Audited Dependencies: All dependencies use permissive OSS licenses
• ✅ Stdio Transport Only: Communication via standard input/output streams

Run Security Audit

Enterprise customers can verify these claims:

# Run full security audit
uv run python -m sef_agents.security_scan

# Output JSON for CI/CD
uv run python -m sef_agents.security_scan --format json

See SECURITY.md for full security policy and architecture details.

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Installation

Prerequisites

• uv or uvx (Install uv)
• Python 3.12+ (Windows users: see WINDOWS_TROUBLESHOOTING.md if encountering installation issues)

Client Compatibility

SEF Agents uses stdio transport (Standard Input/Output). It works with:

• Claude Desktop
• Cursor
• Windsurf
• Any MCP-compatible client supporting stdio

Note: Gemini and GitHub Copilot do not currently support MCP.

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Configuration

Simple installation — works like Playwright MCP. No cloning required.

Cursor (Recommended)

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project-local):

{
  "mcpServers": {
    "sef-agents": {
      "command": "uvx",
      "args": ["sef-agents"]
    }
  }
}

Via UI:

1. Settings → MCP → + Add New MCP Server
2. Name: sef-agents
3. Type: command
4. Command: uvx sef-agents

Claude Desktop

Add to claude_desktop_config.json:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "sef-agents": {
      "command": "uvx",
      "args": ["sef-agents"]
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "sef-agents": {
      "command": "uvx",
      "args": ["sef-agents"]
    }
  }
}

Install from GitHub (Development/Unpublished)

If not yet published to PyPI, use GitHub:

{
  "mcpServers": {
    "sef-agents": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/Mishtert/sef-agents",
        "sef-agents"
      ]
    }
  }
}

Note for Windows users: If you encounter pywin32 access denied errors, see WINDOWS_TROUBLESHOOTING.md for solutions. Prefer using PyPI version (uvx sef-agents) when available.

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Local Development

For contributors or local testing:

git clone https://github.com/Mishtert/sef-agents.git
cd sef-agents
uv sync
uv run sef-agents

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Quick Start

1. Verify Connection

After adding the config, restart your AI assistant. In Cursor:

• Open Settings → MCP
• Look for sef-agents with a green status indicator

2. Try These Commands

Type these in your AI assistant to verify it's working:

"What SEF agents are available?"

Expected: List of 13 agents with descriptions.

"Set my agent to developer"

Expected: Elite Code Quality Protocol injected. AI now enforces coding standards.

"Generate a codemap for this directory"

Expected: CODE_MAP.md structure with files, purposes, dependencies.

"Scan this directory for technical debt"

Expected: Report of TODOs, bare exceptions, missing types, long functions.

3. Full Workflow Example

1. "Set agent to discovery" → Scans codebase, generates documentation
2. "Set agent to product_manager" → Write requirements with testable AC
3. "Set agent to qa_lead" → Validate AC before development
4. "Set agent to developer" → Implement with quality enforcement
5. "Set agent to pr_reviewer" → Review for compliance + AI patterns

Troubleshooting

Issue	Solution
MCP not connecting	Restart AI assistant after config change
uvx not found	Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh
Tools not appearing	Check MCP status in settings; verify JSON syntax
Agent not activating	Use exact agent name: developer

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Contributing

We welcome contributions! Please see CONTRIBUTING.md for:

• Code of conduct
• Development setup
• PR submission guidelines
• Testing requirements

Version History: See GitHub Releases for changelog.

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About

SEF Agents implements the Model Context Protocol (MCP), an open standard developed by Anthropic for connecting AI assistants to external tools and data sources. This ensures compatibility with a wide ecosystem of AI development tools.

SEF Agents is part of the Synchronous Engineering Framework (SEF) — a methodology for collapsing the software delivery lifecycle through intelligent parallelism and agent orchestration.

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License

Proprietary. All rights reserved.