docs: update README and metadata with cohesive voice

Updated copy to create seamless LinkedIn → GitHub experience:

- README hero section: "Because even AI agents need traffic lights"
- Narrative flow: context → problem → solution
- Restructured sections: "Under the hood", "Paperwork", "Works with"
- Updated pyproject.toml description to match tagline
- Subtle humor while staying professional
- Emphasizes traffic control/safety metaphor throughout

Voice is now consistent across all touchpoints.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
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# MCP Multiagent Bridge
### Secure, rate-limited coordination for multiple LLM agents
> *Because even AI agents need traffic lights.*
Lightweight Python MCP server for secure multi-agent coordination with configurable rate limiting, auditable actions, and 4-stage YOLO confirmation flow for safe execution.
Multi-agent systems are already here: backend agents debugging frontend agents, compliance bots reviewing security agents, and specialized models coordinating prod deployments.
But nobody's built the safety layer that keeps them from trampling each other.
> MCP Multiagent Bridge coordinates multiple LLM agents via the Model Context Protocol (MCP). Designed for experiments and small-scale deployments, it provides battle-tested security safeguards without sacrificing developer experience. Use it to prototype agent orchestration securely — plug in Claude, Codex, GPT, or other backends without rewriting core code.
**MCP** is the protocol. **This** is the traffic control system.
> ⚠️ **Beta Software**: Suitable for development/testing. See [Security Policy](SECURITY.md) before production use.
---
## ⚠️ YOLO Mode Warning
## Why it exists
This project includes an optional YOLO mode for command execution. This is inherently dangerous and should only be used:
- In isolated development environments
- With explicit user confirmation
- By users who understand the risks
Multi-agent execution is both powerful and horrifying.
So this bridge adds layered safeguards:
- Environment gate (explicit opt-in)
- Typed confirmation phrase
- One-time validation codes
- Expiring approval tokens (because regret has a TTL)
See [YOLO_MODE.md](YOLO_MODE.md) and [SECURITY.md](SECURITY.md) for details.
> ⚠️ **Beta Software**: Built for development/testing environments with human supervision. See [Security Policy](SECURITY.md) before production use.
## Policy Compliance
---
This project complies with:
- [Anthropic Acceptable Use Policy](https://www.anthropic.com/legal/aup)
- [Anthropic Responsible Scaling Policy](https://www.anthropic.com/responsible-scaling-policy)
## Under the hood
Users are responsible for ensuring appropriate use and maintaining human oversight of all operations.
**Security:**
- HMAC-SHA256 session authentication
- Automatic secret redaction (API keys, passwords, tokens)
- SQLite WAL mode for atomic operations
- Comprehensive audit trail (JSONL format)
- 3-hour conversation expiration
## Security Features ✅
**YOLO Guard™ (4-stage confirmation):**
- Environment gate (`YOLO_MODE=1`)
- Interactive typed confirmation
- One-time validation codes
- Time-limited approval tokens (5-min TTL, single-use)
- Dry-run by default
- **HMAC Authentication**: Session tokens prevent spoofing
- **Automatic Secret Redaction**: Filters API keys, passwords, private keys
- **Atomic Messaging**: SQLite WAL mode prevents race conditions
- **Audit Trail**: All actions logged with timestamps
- **Token Expiration**: Conversations expire after 3 hours
- **Schema Validation**: Strict JSON schemas for all tools
- **No Auto-Execution**: Bridge returns proposals only - no command execution
- **YOLO Guard**: Multi-stage confirmation for command execution (when enabled)
- **Rate Limiting**: 10 req/min, 100 req/hour, 500 req/day per session
**Rate Limiting:**
- Token bucket algorithm
- 10 requests/minute, 100/hour, 500/day
- Per-session tracking with automatic reset
---
## Paperwork
All the boring-but-necessary stuff is here:
- **[LICENSE](LICENSE)** - MIT (do what you want)
- **[SECURITY.md](SECURITY.md)** - Threat model + responsible disclosure
- **[CONTRIBUTING.md](CONTRIBUTING.md)** - How to help
- **Policy compliance** - Anthropic & OpenAI friendly
---
## Works with
Any MCP-compatible LLM:
- Claude (Code, Desktop, API)
- OpenAI models via MCP adapters
- Anthropic API models
- Future: Codex, GPT, custom models
Not tied to any specific backend. Build once, swap models freely.
## Installation

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@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "mcp-multiagent-bridge"
version = "1.0.0-beta"
description = "Python MCP server for secure multi-agent coordination with 4-stage YOLO safeguards and rate limiting"
description = "Secure multi-agent coordination for LLMs — because even AI agents need traffic lights"
readme = "README.md"
license = {text = "MIT"}
authors = [