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Corn Intelligence Server

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A high-performance MCP server integrated with a Django analytics dashboard, featuring 19 tools for AI interaction tracking, AST code analysis, and real-time tok

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Описание

A high-performance MCP server integrated with a Django analytics dashboard, featuring 19 tools for AI interaction tracking, AST code analysis, and real-time token efficiency metrics.

README

A high-performance Model Context Protocol (MCP) server integrated with a Django-powered analytics dashboard. Features the Corn Intelligence toolset for comprehensive AI interaction tracking, AST code analysis, and real-time token efficiency metrics.

🚀 Key Features

1. Intelligence Dashboard

  • Real-time Monitoring: Every tool call is logged with latency, token usage, and efficiency metrics.
  • Auto-Reload: Dashboard refreshes every 15 seconds with a visual countdown indicator.
  • Token Analytics: Visualize direct token costs vs. context savings with efficiency scoring.
  • Session Explorer: Browse and drill into past sessions at /sessions/.

2. Corn Intelligence Toolset (v2.0) — 19 Tools

# Tool Category Description
1 corn_health Core System health — CPU, RAM, uptime
2 corn_session_start Core Begin a tracked work session
3 corn_session_end Core End session with summary
4 corn_memory_store Memory Store agent memory with tags
5 corn_memory_search Memory Keyword search over memories
6 corn_knowledge_store Knowledge Store a shared knowledge item
7 corn_knowledge_search Knowledge Semantic search over knowledge base
8 corn_code_read Code Read raw source code from any file path
9 corn_detect_changes Code Uncommitted git changes cross-referenced with AST graph
10 corn_list_repos Code List indexed repositories with symbol counts (auto-indexes on first call)
11 corn_code_search Code Hybrid AST symbol search by name
12 corn_code_context Code 360° symbol view: callers, callees, hierarchy
13 corn_code_impact Code Blast radius analysis — which files depend on a given file
14 corn_cypher Code Graph-style queries: (a)-[:CALLS]->(b)
15 corn_tool_stats Analytics Usage analytics over last 50 tool calls
16 corn_quality_report Quality Submit a 3-dimension quality report (Clarity/Efficiency/Security)
17 corn_record_conversation Analytics Log raw conversation token usage to Dashboard
18 corn_plan_quality Quality Score a plan text against 8 quality criteria (must ≥80%)
19 corn_changes Analytics Check recent git commits by agents (git log -n 5)

3. AST Code Intelligence Engine

  • Auto-Indexing: corn_list_repos automatically scans and indexes Python source files on first call.
  • Symbol Graph: Stores Function, Class, and Method nodes with CALLS / INHERITS relationships in MySQL.
  • Blast Radius: corn_code_impact identifies all callers transitively affected by changes to a file.

4. Token Efficiency Metrics

  • Accurate Counting: Heuristic blends character density and word count — max(chars/4, words × 1.35) — for reliable estimation across code and natural language.
  • Context Saved: For search tools (memory_search, knowledge_search, code_search), tokens saved = total DB tokens − tokens returned. Reflects real context reduction.
  • Efficiency (%): Saved / (Used + Saved). Aim for >80%!

🏛️ Architecture

IDE (Antigravity / Claude)
    │  stdio (MCP protocol)
    ▼
Docker: personal-mcp-web
    ├── Django MCP Server (run_mcp management command)
    │       └── 19 Corn Intelligence Tools
    ├── AST Indexer (mcp_server/utils/indexer.py)
    └── Django Dashboard (http://localhost:8000)
            └── Real-time Activity Log, Sessions, Token Analytics
    │
    ▼
Docker: mcp_mysql_db (MySQL 8)
    ├── Session, ToolLog
    ├── Memory, Knowledge
    └── Repository, Symbol, SymbolRelation, PlanQuality

🏃 Getting Started

  1. Launch Services:

    docker-compose up -d
    
  2. Connect IDE — add to your MCP config (mcp_config.json):

    {
      "mcpServers": {
        "personal-mcp-v2": {
          "command": "/usr/local/bin/docker",
          "args": ["exec", "-i", "personal-mcp-web", "python", "manage.py", "run_mcp", "--verbosity", "0", "--no-color", "--skip-checks"]
        }
      }
    }
    
  3. Run Migrations (first-time setup):

    docker exec personal-mcp-web python manage.py migrate
    
  4. Explore Dashboard: http://localhost:8000/

🛠️ Development

Apply new migrations after model changes:

docker exec personal-mcp-web python manage.py makemigrations mcp_server
docker exec personal-mcp-web python manage.py migrate mcp_server

Check Django config inside container:

docker exec personal-mcp-web python manage.py check

View live logs:

docker logs -f personal-mcp-web

Powered by Antigravity — Premium AI Engineering.

from github.com/thaivu98/mcp-platform

Установка Corn Intelligence Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/thaivu98/mcp-platform

FAQ

Corn Intelligence Server MCP бесплатный?

Да, Corn Intelligence Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Corn Intelligence Server?

Нет, Corn Intelligence Server работает без API-ключей и переменных окружения.

Corn Intelligence Server — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Corn Intelligence Server в Claude Desktop, Claude Code или Cursor?

Открой Corn Intelligence Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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