Production-ready Python MCP server for secure multi-agent coordination with comprehensive safeguards.
Enables multiple LLM agents (Claude, Codex, GPT, etc.) to collaborate safely through the Model Context Protocol without sharing workspaces or credentials. Built with security-first architecture and production-grade safeguards.
Use cases:
- Backend agent coordinating with frontend agent on different codebases
- Security review agent validating changes from development agent
- Specialized agents collaborating on complex multi-step workflows
- Any scenario requiring isolated agents to communicate securely
Authentication & Authorization:
- HMAC-SHA256 session token authentication
- Automatic secret redaction (API keys, passwords, tokens, private keys)
- 3-hour session expiration with automatic cleanup
- SQLite WAL mode for atomic, race-condition-free operations
4-Stage YOLO Guard™: Command execution (optional) requires multiple confirmation layers:
- Environment gate - explicit
YOLO_MODE=1opt-in - Interactive typed confirmation phrase
- One-time validation code (prevents automation)
- Time-limited approval tokens (5-minute TTL, single-use)
Rate Limiting:
- Token bucket algorithm with configurable windows
- Default: 10 requests/minute, 100/hour, 500/day
- Per-session tracking with automatic reset
- Prevents abuse while allowing legitimate bursts
Audit Trail:
- Comprehensive JSONL logging of all operations
- Timestamps, session IDs, actions, results
- Tamper-evident sequential logging
- Supports compliance and forensic analysis
- Message-only bridge - No auto-execution, returns proposals only
- Schema validation - Strict JSON schemas for all MCP tools
- Command validation - Configurable whitelist/blacklist patterns
- Comprehensive error handling - Graceful degradation, informative errors
- Extensible design - Plugin architecture for future backends
Works with any MCP-compatible LLM:
- Claude Code, Claude Desktop, Claude API
- OpenAI models (via MCP adapters)
- Anthropic API models
- Custom/future models (not tied to specific backend)
# Clone repository
git clone https://github.com/dannystocker/mcp-multiagent-bridge.git
cd mcp-multiagent-bridge
# Install dependencies
pip install mcp>=1.0.0
# Run tests
python test_security.pyFull setup: See QUICKSTART.md
Getting Started:
- QUICKSTART.md - 5-minute setup guide
- EXAMPLE_WORKFLOW.md - Real-world collaboration scenarios
Security & Compliance:
- SECURITY.md - Threat model, responsible disclosure policy
- YOLO_MODE.md - Command execution safety guide
- Policy compliance: Anthropic AUP, OpenAI Usage Policies
Contributing:
- CONTRIBUTING.md - Development setup, PR workflow
- LICENSE - MIT License
- Python 3.11+ - Modern Python with type hints
- SQLite - Atomic operations with WAL mode
- MCP Protocol - Model Context Protocol integration
- pytest - Comprehensive test suite
- CI/CD - GitHub Actions (tests, security scanning, linting)
- Lines of Code: ~5,200 (including tests + documentation)
- Test Coverage: Core security components verified
- Documentation: 2,000+ lines across 7 markdown files
- Dependencies: 1 (mcp, pinned for reproducibility)
- License: MIT
# Install dev dependencies
pip install -r requirements.txt
# Install pre-commit hooks
pip install pre-commit
pre-commit install
# Run test suite
pytest
# Run security tests
python test_security.pySee CONTRIBUTING.md for complete development workflow.
Recommended for:
- Development and testing workflows
- Isolated workspaces
- Human-supervised operations
- Prototype multi-agent systems
Not recommended for:
- Production systems without additional safeguards
- Unattended automation
- Critical infrastructure
- Environments with untrusted agents
See SECURITY.md for complete security considerations and threat model.
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Security: See SECURITY.md for responsible disclosure
MIT License - Copyright © 2025 Danny Stocker
See LICENSE for full terms.
Built with Claude Code and Model Context Protocol.
