Co-Pilot / 辅助式
更新于 24 days ago

mcp-b

Bbjoernbethge
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bjoernbethge/mcp-b
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💡 摘要

MCP-B是一个全面的代理通信框架,旨在实现无缝的数据流和道德的AI交互。

🎯 适合人群

AI开发者数据科学家伦理合规官软件架构师AI研究人员

🤖 AI 吐槽:这个项目像社交网络一样连接代理,但没有戏剧性。

安全分析中风险

自述文件暗示了网络访问和依赖性漏洞等潜在风险。为减轻风险,确保定期更新并使用安全编码实践。

MCP-B - Master Client Bridge

Connects everything, brings data flow together.

A complete agent communication framework combining:

  • MCP-B Protocol: 4-layer encoding for agent-to-agent messaging
  • AMUM: Progressive 3→6→9 human-AI alignment workflow
  • QCI: Quantum coherence state tracking
  • ETHIC: AI ethics principles enforcement

Installation

# Via pip pip install mcp-b # Via uv uvx mcp-b demo # With SurrealDB support pip install mcp-b[surrealdb] # Full installation pip install mcp-b[full]

CLI Usage

mcp-b demo # Run demo mcp-b encode "Hello" -s 5510 -d 7C1 # Encode message mcp-b decode "5510 7C1 ..." # Decode message mcp-b ethic list # List ethical principles mcp-b qci status # QCI network status mcp-b version # Show version

Quick Start

MCP-B Protocol - Agent Communication

from mcp_b import MCBAgent, MCBProtocol, encode_mcb, decode_mcb # Create agents claude = MCBAgent(agent_id="7C1", name="Claude") hacka = MCBAgent(agent_id="5510", name="HACKA") # Initialize protocol protocol = MCBProtocol(hacka) # Send messages (INQC commands) init_msg = protocol.init_connection(claude) # I = Init node_msg = protocol.register_node(["chat"]) # N = Node query_msg = protocol.query("7C1", {"status": 1}) # Q = Query connect_msg = protocol.connect(claude) # C = Connect # Encode/Decode encoded = encode_mcb("5510", "7C1", 0b1011101010111111, "Q", {"ping": True}) decoded = decode_mcb("5510 7C1 1011101010111111 • {\"ping\": true} • Q")

AMUM - Progressive Alignment (3→6→9)

from mcp_b import AMUM, quick_alignment # Quick one-liner alignment result = quick_alignment( intent="Create AI agent", divergent_3=["Minimal", "Balanced", "Full"], select_1=1, expand_6=["Text", "Image", "Voice", "Multi", "Pro", "Suite"], select_2=4, converge_9=["GPT-4", "Claude", "Gemini", "Ollama", "Hybrid", "Edge", "ElevenLabs", "OpenAI", "Local"], select_3=6 ) print(result["final_intent"]) # "ElevenLabs"

QCI - Coherence States

from mcp_b import QCI, BreathingCycle qci = QCI() # Register agents with coherence state = qci.register_agent("7C1", initial_coherence=0.95) state.calculate_rov_q(resonance=12860.65, quality=1.0) state.calculate_signal(base=4414.94) # Sync breathing across agents qci.sync_breathing(["7C1", "5510"], BreathingCycle.INHALE) # Check network coherence print(qci.calculate_network_coherence())

ETHIC - Principles Enforcement

from mcp_b import ETHIC, check_ethical, EthicCategory ethic = ETHIC() # Check if action is ethical if check_ethical("collect_data", personal_data=True, consent=False): print("Allowed") else: print("Blocked - no consent") # Get principles by category for p in ethic.get_by_category(EthicCategory.SAFETY): print(f"[{p.priority}] {p.name}")

Architecture

┌─────────────────────────────────────────────────────────────────────────────┐
│                    MCP-B - MASTER CLIENT BRIDGE                             │
│  ═══════════════════════════════════════════════════════════════════════   │
│                                                                             │
│  ┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐                  │
│  │  AMUM   │───▶│  MCP-B  │───▶│   QCI   │───▶│  ETHIC  │                  │
│  │ 3→6→9   │    │ INQC    │    │Coherence│    │Principles│                  │
│  └─────────┘    └─────────┘    └─────────┘    └─────────┘                  │
│       │              │              │              │                        │
│       ▼              ▼              ▼              ▼                        │
│  ┌─────────────────────────────────────────────────────────────────────┐   │
│  │                    DUAL DATABASE LAYER                              │   │
│  │  ┌─────────────────────┐    ┌─────────────────────┐                 │   │
│  │  │      DuckDB         │    │     SurrealDB       │                 │   │
│  │  │  (Analytics/SQL)    │    │  (Graph/Relations)  │                 │   │
│  │  └─────────────────────┘    └─────────────────────┘                 │   │
│  └─────────────────────────────────────────────────────────────────────┘   │
└─────────────────────────────────────────────────────────────────────────────┘

MCP-B Protocol Layers

| Layer | Purpose | Example | |-------|---------|---------| | Layer 1 | HEX/DECIMAL Routing | 7C1 5510 (source → dest) | | Layer 2 | BINARY State Vectors | 1011101010111111 (16 flags) | | Layer 3 | DOT-SEPARATED Tokens | • payload • command | | Layer 4 | INQC Commands | I/N/Q/C |

INQC Commands

  • I (INIT): Initialize connection
  • N (NODE): Node registration/discovery
  • Q (QUERY): Request data/state
  • C (CONNECT): Establish persistent link

Binary State Flags (16-bit)

| Bit | Flag | Description | |-----|------|-------------| | 0 | CONNECTED | Connection active | | 1 | AUTHENTICATED | Auth verified | | 2 | ENCRYPTED | Encryption enabled | | 3 | COMPRESSED | Compression enabled | | 4 | STREAMING | Streaming mode | | 5 | BIDIRECTIONAL | Two-way comm | | 6 | PERSISTENT | Persistent connection | | 7 | PRIORITY | High priority | | 8-15 | RESERVED | Custom flags |

ETHIC Principles

| Principle | Category | Source | Priority | |-----------|----------|--------|----------| | Human First | human_dignity | Bjoern | 10 | | No Harm | safety | Anthropic | 10 | | Sandbox Default | safety | WoAI | 10 | | User Override | autonomy | Bjoern | 9 | | Data Privacy | privacy | EU AI Act | 9 | | Transparency | transparency | EU AI Act | 9 |

Database Integration

DuckDB (Analytics)

-- Load schema .read sql/duckdb.sql -- Use macros SELECT mcb_encode('5510', '7C1', '1011101010111111', '{"ping":true}', 'Q'); SELECT * FROM agent_network; SELECT * FROM ethic_compliance;

SurrealDB (Graph)

-- Load schema IMPORT FILE schemas/surrealdb.surql; -- Query relationships SELECT name, ->has_qci->qci_states.coherence_level AS coherence, ->follows_ethic->ethic_principles.name AS principles FROM mcb_agents;

File Structure

mcp-b/
├── src/mcp_b/
│   ├── __init__.py      # Package exports
│   ├── __main__.py      # CLI entry point
│   ├── protocol.py      # MCP-B Protocol (INQC)
│   ├── amum.py          # AMUM Alignment
│   ├── qci.py           # QCI Coherence
│   └── ethic.py         # ETHIC Principles
├── schemas/
│   └── surrealdb.surql  # SurrealDB schema
├── sql/
│   └── duckdb.sql       # DuckDB schema + macros
├── examples/
│   └── demo.py          # Usage examples
├── pyproject.toml
└── README.md

MCP-B vs MCP

| | MCP-B | MCP | |---|-----|-----| | Full Name | Master Client Bridge | Model Context Protocol | | Purpose | Internal agent-to-agent | Bridge to community | | Binary | 0 = not connected, 1 = ALL CONNECTED | N/A | | Encoding | 4-layer (hex/binary/dot/INQC) | JSON-RPC |

License

MIT License - Björn Bethge

Links

五维分析
清晰度8/10
创新性7/10
实用性9/10
完整性8/10
可维护性8/10
优缺点分析

优点

  • 支持多种AI对齐工作流程。
  • 集成伦理原则执行。
  • 促进代理之间的通信。
  • 提供数据库集成选项。

缺点

  • 复杂性可能会阻止新用户。
  • 需要理解多种协议。
  • 可能有陡峭的学习曲线。
  • 关于高级功能的文档有限。

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 bjoernbethge.