CodeGraph CLI MCP Server

# Qwen2.5-Coder-14B-128K Configuration for CodeGraph MCP # Model: hf.co/unsloth/Qwen2.5-Coder-14B-Instruct-128K-GGUF:Q4_K_M [qwen_model] # Model configuration model_name = "qwen2.5-coder-14b-128k" base_url = "http://localhost:11434" context_window = 128000 max_tokens = 8192 temperature = 0.1 timeout_seconds = 90 [model_info] # Model specifications parameters = "14B" quantization = "Q4_K_M" context_length = 128000 memory_requirement = "24GB VRAM" performance_class = "SOTA_14B" specialization = "Code Analysis and Understanding" [installation] # Installation command ollama_command = "ollama pull hf.co/unsloth/Qwen2.5-Coder-14B-Instruct-128K-GGUF:Q4_K_M" alternative_name = "qwen2.5-coder-14b-128k" download_size = "8.4GB" recommended_ram = "32GB" [capabilities] # What Qwen2.5-Coder can do for CodeGraph semantic_analysis = true pattern_detection = true architectural_understanding = true impact_analysis = true team_convention_analysis = true comprehensive_codebase_analysis = true code_quality_assessment = true [performance_targets] # Performance expectations semantic_search_time = 2000 # 2 seconds for semantic search analysis comprehensive_analysis = 5000 # 5 seconds for full codebase analysis context_utilization = 0.8 # Use 80% of 128K context window quality_threshold = 0.9 # 90% minimum confidence score max_concurrent_requests = 3 # Limit concurrent requests for memory [prompts] # Prompt optimization settings system_prompt_semantic = "You are Qwen2.5-Coder providing semantic code analysis for MCP-calling LLMs. Focus on understanding code purpose, patterns, and architectural context." system_prompt_comprehensive = "You are Qwen2.5-Coder providing comprehensive codebase analysis. Use your 128K context window for complete understanding." system_prompt_patterns = "You are Qwen2.5-Coder analyzing code patterns for consistency and quality. Provide actionable guidance for code generation." [mcp_integration] # MCP-specific settings tool_prefix = "codegraph" available_tools = [ "semantic_intelligence", "enhanced_search", "pattern_analysis", "impact_assessment" ] recommended_clients = ["claude", "gpt-4", "custom-agents"]