AGI模型上下文协议服务器

# Already configured in ~/.claude.json
# Restart Claude Code to activate

# Record a task outcome
agi_record_outcome(
    task_id="task_001",
    task_type="code_generation",
    agent_used="coder",
    success=True,
    execution_time_ms=1500,
    quality_score=0.9
)

# Get agent recommendation
agi_recommend_agent(
    task_type="code_generation"
)
# Returns: {"recommended_agent": "coder", "confidence": 0.85}

# Execute a complex task
agi_execute_task(
    description="Implement user authentication with JWT tokens",
    task_type="code_generation"
)
# Returns: Decomposed subtasks with execution results

# Register a new skill
agi_register_skill(
    skill_name="data_processor",
    code="def process(data): return [x*2 for x in data if x > 0]",
    description="Optimized data processor"
)

# Start A/B test
agi_start_ab_test(
    skill_name="data_processor",
    version_a="v1",
    version_b="v2",
    split_ratio=0.5
)

# Execute a high-level goal
agi_execute_goal(
    goal_description="Build a REST API for user management",
    context={"language": "Python", "framework": "FastAPI"}
)
# Returns: Decomposed tasks with dependencies and estimates

# Synthesize context
agi_synthesize_context(
    query="multi-agent coordination implementation",
    source_types=["file", "memory", "code"],
    target_tokens=10000
)
# Returns: Compressed context with relevance scores

# Propose an improvement
agi_propose_modification(
    code_before="def old_algo(): ...",
    code_after="def new_algo(): ...",
    modification_type="algorithm_improve",
    description="Optimize from O(n²) to O(n)"
)
# Returns: Modification ID with proof status

{
  "mcpServers": {
    "agi-mcp": {
      "command": "python3",
      "args": [
        "/Volumes/SSDRAID0/agentic-system/mcp-servers/agi-mcp/server.py"
      ],
      "description": "AGI System - Meta-learning, multi-agent coordination, skill evolution, goal decomposition, context synthesis, and Darwin Gödel self-improvement"
    }
  }
}

Claude Code
    ↓
AGI MCP Server (21 tools)
    ↓
┌─────────────────────────────────────┐
│  Meta-Learning Engine               │
│  Multi-Agent Coordinator            │
│  Skill Evolution System             │
│  Goal Decomposition AI              │
│  Context Synthesis Engine           │
│  Darwin Gödel Machine               │
└─────────────────────────────────────┘
    ↓
Databases + Enhanced Memory + SAFLA

# Test imports
python3 -c "import sys; sys.path.insert(0, '/Volumes/SSDRAID0/agentic-system/intelligent-agents'); from meta_learning_engine import *; from multi_agent_coordinator import *; print('✓ All imports successful')"

# Test server startup
python3 /Volumes/SSDRAID0/agentic-system/mcp-servers/agi-mcp/server.py