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CornMCP

★ 65 Open GitHub ↗

CornMCP is an open-source mono repo that gives AI coding agents (Antigravity, Cursor, Claude Code, Codex), token-saving access to your codebase through the Model Context Protocol (MCP).

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# 🌽 CornMCP

**The AI Agent Intelligence Platform — MCP Server + Analytics Dashboard**

> Surgical code intelligence. Semantic memory. Quality enforcement.
> Stop burning tokens on full-file reads. Start extracting exactly what your agent needs.

[![Node.js](https://img.shields.io/badge/Node.js-22+-339933?logo=node.js&logoColor=white)](https://nodejs.org)
[![TypeScript](https://img.shields.io/badge/TypeScript-5.x-3178C6?logo=typescript&logoColor=white)](https://typescriptlang.org)
[![MCP](https://img.shields.io/badge/MCP-1.x-purple)](https://modelcontextprotocol.io)
[![License](https://img.shields.io/badge/License-MIT-yellow)](https://raw.githubusercontent.com/yuki-20/CornMCP/master/LICENSE)

---

## What is CornMCP?

Corn Hub is a **Model Context Protocol (MCP) server** and real-time **analytics dashboard** that gives AI coding agents (Antigravity, Cursor, Claude Code, Codex) surgical access to your codebase through 18 specialized tools.

Instead of dumping entire files into the context window, CornMCP provides:

- 🧠 **Semantic Memory** — Agents remember across sessions via vector search
- 🔍 **Native AST Engine** — Real call graphs, type hierarchies, and symbol-level analysis via TypeScript Compiler API
- 📋 **Quality Gates** — Plans must score ≥80% before execution
- 📊 **Live Analytics** — Track every tool call, latency, and token savings
- 🔄 **Multi-Agent Awareness** — Agents see each other's changes in real-time
- 💾 **Zero External Dependencies** — No external services. Everything runs locally with SQLite.

---

## Architecture

### 1. System Overview

> How the three services connect and communicate.

```mermaid
graph TB
 subgraph IDE["🖥️ Your IDE"]
 Agent["🤖 AI Agent (Antigravity / Cursor / Claude)"]
 end

subgraph MCP["🌽 corn-mcp :8317"]
 direction TB
 Transport["Streamable HTTP Transport /mcp endpoint"]
 Auth["API Key Auth middleware/auth.ts"]
 Tools["18 MCP Tools"]
 Telemetry["Telemetry Interceptor Logs every tool call"]

subgraph ToolGroups["Tool Modules"]
 Memory["🧠 memory.ts store / search"]
 Knowledge["📚 knowledge.ts store / search"]
 Code["🔍 code.ts search / read / context impact / cypher"]
 Quality["📋 quality.ts plan_quality / report"]
 Session["🔄 session.ts start / end"]
 Analytics["📊 analytics.ts tool_stats"]
 Changes["🔀 changes.ts changes / detect"]
 Health["💚 health.ts health / list_repos"]
 end
 end

subgraph API["⚡ corn-api :4000"]
 direction TB
 Hono["Hono REST API"]
 Routes["15 Route Modules"]
 AST["Native AST Engine TypeScript Compiler API"]
 SQLite[("💾 SQLite corn.db")]
 VectorDB[("🧲 SQLite Vector Store mem9-vectors.db")]
 end

subgraph Dashboard["📊 corn-web :3000"]
 NextJS["Next.js 16 Dashboard Turbopack"]
 end

subgraph Embeddings["☁️ External (Optional)"]
 Voyage["Voyage AI API voyage-code-3"]
 end

Agent -->|"JSON-RPC over HTTP Bearer Token"| Transport
 Transport --> Auth
 Auth --> Tools
 Tools --> Telemetry
 Telemetry -->|"POST /api/metrics/query-log"| Hono

Memory -->|"Embeds + stores vectors"| VectorDB
    Memory -.->|"Optional: Voyage AI"| Voyage
    Knowledge -->|"Embeds + stores vectors"| VectorDB
    Code -->|"POST /api/intel/*"| Hono
    Quality -->|"POST /api/quality/*"| Hono
    Session -->|"POST /api/sessions/*"| Hono
    Analytics -->|"GET /api/analytics/*"| Hono
    Changes -->|"POST /api/intel/detect-changes"| Hono
    Health -->|"GET /health"| Hono

Hono --> Routes
    Routes --> AST
    Routes --> SQLite
    AST --> SQLite
    NextJS -->|"fetch() to :4000"| Hono

style IDE fill:#1a1a2e,stroke:#e94560,color:#fff
    style MCP fill:#16213e,stroke:#0f3460,color:#fff
    style API fill:#0f3460,stroke:#533483,color:#fff
    style Dashboard fill:#533483,stroke:#e94560,color:#fff
    style Embeddings fill:#2d2d2d,stroke:#666,color:#aaa
```

#### How It Works

| Connection | Protocol | Description |
|-----------|----------|-------------|
| **IDE → corn-mcp** | JSON-RPC over HTTP | AI agent sends tool calls via MCP SDK. Bearer token auth required. |
| **corn-mcp → corn-api** | REST HTTP (fetch) | Tool handlers call Dashboard API endpoints for data persistence. |
| **corn-mcp → SQLite vectors** | Direct file I/O | Memory and knowledge tools embed content and store vectors locally. |
| **corn-mcp → Voyage AI** | HTTPS API | Optional: semantic embeddings for memory/knowledge search. Falls back to local hash if unavailable. |
| **corn-api → SQLite** | sql.js (in-process) | All data stored in `./data/corn.db` — sessions, quality, code graph, analytics. |
| **corn-web → corn-api** | REST HTTP (fetch) | Dashboard fetches data from `:4000` API for real-time visualization. |
| **Telemetry** | Fire-and-forget POST | Every tool call logs to `/api/metrics/query-log` for analytics dashboard. |

---

### 2. MCP Request Lifecycle

> What happens step-by-step when your AI agent calls a Corn Hub tool.

```mermaid
sequenceDiagram
    participant Agent as 🤖 AI Agent
    participant IDE as 🖥️ IDE (MCP Client)
    participant MCP as 🌽 corn-mcp
    participant Auth as 🔐 Auth Middleware
    participant Tool as 🔧 Tool Handler
    participant API as ⚡ corn-api
    participant DB as 💾 SQLite
    participant Vec as 🧲 Vector Store
    participant Embed as ☁️ Embeddings

Note over Agent,IDE: Agent decides to call corn_memory_store

Agent->>IDE: tools/call {name: "corn_memory_store", params: {...}}
    IDE->>MCP: POST /mcp (JSON-RPC, Bearer token)

MCP->>Auth: validateApiKey(request)
    Auth-->>MCP: ✅ valid (agentId: "local-ide")

MCP->>MCP: createMcpServer(env)
    MCP->>MCP: new WebStandardStreamableHTTPServerTransport()
    MCP->>MCP: mcpServer.connect(transport)

MCP->>Tool: corn_memory_store({content, projectId, tags})

Tool->>Embed: embed(["memory content"])
    alt Voyage AI available
        Embed-->>Tool: [0.12, -0.34, 0.56, ...] (1024 dims)
    else Fallback
        Embed-->>Tool: [hash-based vector] (256 dims)
    end

Tool->>Vec: INSERT INTO vectors (id, embedding, payload)
    Vec-->>Tool: ✅ stored

Tool-->>MCP: {content: [{type: "text", text: "✅ Memory stored (id: mem-abc123)"}]}

MCP->>API: POST /api/metrics/query-log (fire-and-forget telemetry)
    Note over API: Logs: tool=corn_memory_store, status=ok, latency=401ms

MCP-->>IDE: JSON-RPC response
    IDE-->>Agent: Tool result displayed

Note over Agent: Agent continues with stored memory context
```

#### Key Details

- **Stateless**: Each request creates a fresh `McpServer` instance — no session state on the server
- **Auth**: Bearer token validated against API keys stored in `corn-api` database
- **Telemetry**: Every tool call is logged (tool name, status, latency, input size) as fire-and-forget
- **Embedding Fallback**: If Voyage AI is rate-limited or unavailable, auto-rotates models then falls back to local hash embeddings
- **Model Rotation**: `voyage-code-3` → `voyage-4-large` → `voyage-4` → `voyage-code-2` → `voyage-4-lite`

---

### 3. The 18 MCP Tools — Categories & Data Flow

> Every tool grouped by category, showing what backend each one hits.

```mermaid
graph LR
    subgraph Agent["🤖 AI Agent"]
        Call["Tool Call"]
    end

subgraph Memory["🧠 Memory (2 tools)"]
        MS["corn_memory_store"]
        MR["corn_memory_search"]
    end

subgraph Knowledge["📚 Knowledge (2 tools)"]
        KS["corn_knowledge_store"]
        KR["corn_knowledge_search"]
    end

subgraph CodeIntel["🔍 Code Intelligence (7 tools)"]
        CS["corn_code_search"]
        CR["corn_code_read"]
        CC["corn_code_context"]
        CI["corn_code_impact"]
        CY["corn_cypher"]
        LR2["corn_list_repos"]
        DC["corn_detect_changes"]
    end

subgraph QualityGates["📋 Quality (2 tools)"]
        PQ["corn_plan_quality"]
        QR2["corn_quality_report"]
    end

subgraph Sessions["🔄 Sessions (2 tools)"]
        SS["corn_session_start"]
        SE["corn_session_end"]
    end

subgraph Analytics2["📊 Analytics (2 tools)"]
        TS["corn_tool_stats"]
        CH["corn_changes"]
    end

subgraph Health2["💚 Health (1 tool)"]
        HE["corn_health"]
    end

subgraph Backends["Backends"]
 VecDB[("🧲 Vector Store SQLite")]
 APIDB[("💾 corn-api SQLite")]
 AST2["🏗️ AST Engine"]
 Git["📂 Git CLI"]
 end

Call --> Memory & Knowledge & CodeIntel & QualityGates & Sessions & Analytics2 & Health2

MS & MR --> VecDB
    KS & KR --> VecDB
    CS & CC & CI & CY & LR2 --> APIDB
    CS & CC & CI --> AST2
    CR --> Git
    DC --> Git
    DC --> AST2
    PQ & QR2 --> APIDB
    SS & SE --> APIDB
    TS --> APIDB
    CH --> APIDB
    HE --> APIDB

style Agent fill:#e94560,stroke:#e94560,color:#fff
    style Memory fill:#1a1a2e,stroke:#0f3460,color:#fff
    style Knowledge fill:#1a1a2e,stroke:#0f3460,color:#fff
    style CodeIntel fill:#16213e,stroke:#533483,color:#fff
    style QualityGates fill:#0f3460,stroke:#e94560,color:#fff
    style Sessions fill:#533483,stroke:#e94560,color:#fff
    style Analytics2 fill:#2d2d2d,stroke:#666,color:#fff
    style Health2 fill:#1b4332,stroke:#2d6a4f,color:#fff
```

#### Tool Reference

| # | Tool | Category | Backend | Description |
|---|------|----------|---------|-------------|
| 1 | `corn_health` | Health | API | System health — services, uptime, version |
| 2 | `corn_list_repos` | Code | API + AST | List indexed repositories with symbol counts |
| 3 | `corn_code_search` | Code | AST → SQLite | Hybrid vector/AST symbol search |
| 4 | `corn_code_read` | Code | Filesystem | Read raw source code from indexed repos |
| 5 | `corn_code_context` | Code | AST → SQLite | 360° symbol view: callers, callees, hierarchy |
| 6 | `corn_code_impact` | Code | AST → SQLite | Blast radius analysis with recursive CTE |
| 7 | `corn_cypher` | Code | AST → SQLite | Cypher-to-SQL graph queries |
| 8 | `corn_detect_changes` | Code | Git + AST | Uncommitted changes cross-referenced with graph |
| 9 | `corn_memory_store` | Memory | Vector DB | Store agent memory with embedding |
| 10 | `corn_memory_search` | Memory | Vector DB | Semantic similarity search over memories |
| 11 | `corn_knowledge_store` | Knowledge | Vector DB | Store shared knowledge item |
| 12 | `corn_knowledge_search` | Knowledge | Vector DB | Semantic search over knowledge base |
| 13 | `corn_plan_quality` | Quality | API SQLite | Score a plan against 8 criteria (must ≥80%) |
| 14 | `corn_quality_report` | Quality | API SQLite | Submit 4-dimension quality report (must ≥80%) |
| 15 | `corn_session_start` | Session | API SQLite | Begin tracked work session |
| 16 | `corn_session_end` | Session | API SQLite | End session with summary and decisions |
| 17 | `corn_tool_stats` | Analytics | API SQLite | View tool usage analytics and trends |
| 18 | `corn_changes` | Analytics | API SQLite | Check for recent commits by other agents |

---

### 4. Data Flow — From Code to Intelligence

> How your codebase becomes a queryable knowledge graph.

```mermaid
flowchart TD
    subgraph Input["📂 Your Codebase"]
        Files["*.ts, *.tsx, *.js, *.jsx files"]
    end

subgraph Indexing["🏗️ AST Engine (ast-engine.ts)"]
 Collect["collectFiles() Recursively scan project Skip: node_modules, dist, .git"]
 Parse["ts.createProgram() TypeScript Compiler API Full type-aware parsing"]
 Extract["AST Walk Extract symbols + edges"]
 Store["SQLite Persist INSERT into code_symbols INSERT into code_edges"]
 end

subgraph Symbols["📊 Extracted Data"]
 SymTable["code_symbols table 965 rows"]
 EdgeTable["code_edges table 407 rows"]
 end

subgraph Queries["🔍 Query Layer (intel.ts)"]
 Search["searchSymbols() LIKE + ranking"]
 Context["getSymbolContext() JOIN callers/callees/imports"]
 Impact["getSymbolImpact() Recursive CTE traversal"]
 Cypher["executeCypher() Cypher → SQL translation"]
 end

subgraph MCPTools["🌽 MCP Tool Surface"]
        T1["corn_code_search"]
        T2["corn_code_context"]
        T3["corn_code_impact"]
        T4["corn_cypher"]
    end

subgraph AgentUse["🤖 Agent Uses"]
 Understand["Understand codebase architecture"]
 PlanChanges["Plan changes with blast radius awareness"]
 Navigate["Navigate call graphs and dependencies"]
 Refactor["Safe refactoring with impact analysis"]
 end

Files --> Collect --> Parse --> Extract --> Store
    Store --> SymTable & EdgeTable
    SymTable & EdgeTable --> Search & Context & Impact & Cypher
    Search --> T1
    Context --> T2
    Impact --> T3
    Cypher --> T4
    T1 --> Understand
    T2 --> Navigate
    T3 --> PlanChanges
    T4 --> Refactor

style Input fill:#1a1a2e,stroke:#e94560,color:#fff
    style Indexing fill:#16213e,stroke:#0f3460,color:#fff
    style Symbols fill:#0f3460,stroke:#533483,color:#fff
    style Queries fill:#533483,stroke:#e94560,color:#fff
    style MCPTools fill:#e94560,stroke:#fff,color:#fff
    style AgentUse fill:#2d6a4f,stroke:#40916c,color:#fff
```

#### Symbol Extraction Details

| Symbol Kind | Example | What's Captured |
|-------------|---------|-----------------|
| **Function** | `createLogger()` | Name, params, return type, file, lines, exported?, signature |
| **Class** | `CornError` | Name, extends, implements, methods, properties |
| **Interface** | `Logger` | Name, members, extends |
| **Type** | `LogLevel` | Name, definition |
| **Enum** | `HttpStatus` | Name, members |
| **Variable** | `app` | Name, type annotation, initializer |

#### Edge Types

| Edge | Meaning | Example |
|------|---------|---------|
| `calls` | Function A calls Function B | `start()` → `getDb()` |
| `imports` | File A imports from File B | `index.ts` → `@corn/shared-utils` |
| `extends` | Class A extends Class B | `NotFoundError` → `CornError` |
| `implements` | Class implements Interface | `LocalHashEmbeddingProvider` → `EmbeddingProvider` |

> **Performance**: Corn Hub indexes itself (49 files) in ~2 seconds, extracting 965 symbols and 407 edges.

---

## Project Structure

```
corn-hub/
├── apps/
│   ├── corn-api/              # Dashboard REST API (Hono + SQLite)
│   │   └── src/
│   │       ├── index.ts       # Server entry, health checks
│   │       ├── db/
│   │       │   ├── client.ts  # SQLite client (sql.js)
│   │       │   └── schema.sql # Database schema (code_symbols, code_edges, etc.)
│   │       ├── services/
│   │       │   └── ast-engine.ts  # 🆕 Native TypeScript Compiler API AST engine
│   │       └── routes/
│   │           ├── intel.ts      # Code intelligence (search, context, impact, cypher)
│   │           ├── indexing.ts   # Trigger AST analysis for projects
│   │           ├── analytics.ts  # Tool usage analytics
│   │           ├── knowledge.ts  # Knowledge base CRUD
│   │           ├── projects.ts   # Project management
│   │           ├── providers.ts  # LLM provider accounts
│   │           ├── quality.ts    # 4D quality reports
│   │           ├── sessions.ts   # Agent session tracking
│   │           ├── setup.ts      # System info
│   │           ├── stats.ts      # Dashboard metrics
│   │           ├── system.ts     # System metrics (CPU, memory)
│   │           ├── usage.ts      # Token usage tracking
│   │           └── webhooks.ts   # Webhook endpoints
│   │
│   ├── corn-mcp/              # MCP Server (18 tools)
│   │   └── src/
│   │       ├── cli.ts         # STDIO transport + telemetry interceptor
│   │       ├── index.ts       # Server factory + tool registration
│   │       ├── node.ts        # HTTP transport entry point
│   │       └── tools/
│   │           ├── analytics.ts   # corn_tool_stats
│   │           ├── changes.ts     # corn_changes, corn_detect_changes
│   │           ├── code.ts        # corn_code_search/read/context/impact, corn_cypher
│   │           ├── health.ts      # corn_health
│   │           ├── knowledge.ts   # corn_knowledge_search/store
│   │           ├── memory.ts      # corn_memory_search/store
│   │           ├── quality.ts     # corn_plan_quality, corn_quality_report
│   │           └── sessions.ts    # corn_session_start/end
│   │
│   └── corn-web/              # Analytics Dashboard (Next.js 16)
│       └── src/
│           ├── app/
│           │   ├── page.tsx       # Main dashboard
│           │   ├── quality/       # Quality reports & grade trends
│           │   ├── sessions/      # Agent session history
│           │   ├── usage/         # Token usage analytics
│           │   ├── knowledge/     # Knowledge base viewer
│           │   ├── projects/      # Project management
│           │   ├── installation/  # IDE setup guide
│           │   └── settings/      # Configuration
│           ├── components/
│           │   └── layout/        # Glassmorphic dashboard shell
│           └── lib/
│               └── api.ts         # API client
│
├── packages/
│   ├── shared-mem9/           # Vector DB + Embedding Provider
│   │   └── src/index.ts       # SQLite vector store, model rotation,
│   │                          # OpenAI/Voyage embeddings, hash fallback
│   ├── shared-types/          # Shared TypeScript interfaces
│   └── shared-utils/          # Logger, ID gen, error classes
│
├── infra/
│   ├── docker-compose.yml     # Optional Docker stack
│   ├── Dockerfile.corn-api
│   ├── Dockerfile.corn-mcp
│   ├── Dockerfile.corn-web
│   └── nginx-dashboard.conf
│
└── .agent/
    └── workflows/
        └── corn-quality-gates.md  # Mandatory AI quality workflow
```

---

## Native AST Engine

Corn Hub includes a **built-in TypeScript Compiler API engine** that provides real code intelligence — no external services needed.

### What It Extracts

| Category | Details |
|----------|---------|
| **Symbols** | Functions, classes, interfaces, types, enums, variables, methods, properties |
| **Edges** | Function calls, imports, extends, implements |
| **Metadata** | File paths, line ranges, export status, signatures, JSDoc comments |

### How It Works

```
Local Project Directory
        │
        ▼
  collectFiles()          Recursively find all .ts/.tsx/.js/.jsx files
        │                 (skips node_modules, dist, .git, etc.)
        ▼
  ts.createProgram()      TypeScript Compiler API parses all files
        │
        ▼
  AST Walk                Extract symbols + build dependency edges
        │
        ▼
  SQLite Storage          INSERT into code_symbols + code_edges tables
        │
        ▼
  Query Functions         searchSymbols, getSymbolContext, getSymbolImpact,
                          executeCypher, getProjectStats
```

### Capabilities

- **Call Graph**: Who calls `dbRun`? → 8 callers across 5 files with exact line numbers
- **Impact Analysis**: What breaks if I change `createLogger`? → Recursive CTE traces 6 downstream symbols
- **Cypher Queries**: `MATCH (n:class) RETURN n` → Finds all 10 classes in the codebase
- **Import Mapping**: Which files import from `shared-utils`? → Full dependency graph
- **Type Hierarchies**: `CornError` → `NotFoundError`, `UnauthorizedError`, `ValidationError`

### Self-Indexing Results (Corn Hub itself)

| Metric | Value |
|--------|------:|
| Files Analyzed | 49 |
| Symbols Extracted | 965 |
| Edges Built | 407 |
| By Kind | 764 variables, 111 functions, 32 interfaces, 28 methods, 16 properties, 10 classes, 1 type |
| Analysis Time | ~2 seconds |

---

## MCP Tools Reference

Corn Hub exposes **18 tools** via the Model Context Protocol:

### 🧠 Memory & Knowledge

| Tool | Description |
|------|-------------|
| `corn_memory_store` | Store a memory for cross-session recall |
| `corn_memory_search` | Semantic search across all agent memories |
| `corn_knowledge_store` | Save reusable patterns, decisions, bug fixes |
| `corn_knowledge_search` | Search the shared knowledge base |

### 🔍 Code Intelligence (AST-Powered)

| Tool | Description |
|------|-------------|
| `corn_code_search` | Hybrid vector + AST search across the codebase |
| `corn_code_read` | Read raw source from indexed repos with line ranges |
| `corn_code_context` | 360° view of a symbol: callers, callees, imports, hierarchy |
| `corn_code_impact` | Blast radius analysis — recursive CTE on dependency edges |
| `corn_cypher` | Cypher-like queries translated to SQL against the code graph |
| `corn_detect_changes` | Analyze uncommitted changes + cross-reference with indexed symbols |
| `corn_list_repos` | List all indexed repositories with symbol/edge counts |

### 📋 Quality & Sessions

| Tool | Description |
|------|-------------|
| `corn_plan_quality` | Score a plan against 8 criteria (must pass ≥80%) |
| `corn_quality_report` | Submit 4D quality scores (Build, Regression, Standards, Traceability) |
| `corn_session_start` | Begin a tracked work session |
| `corn_session_end` | End session with summary, files changed, decisions |
| `corn_changes` | Check for recent changes from other agents |

### 📊 Analytics & System

| Tool | Description |
|------|-------------|
| `corn_tool_stats` | View tool usage analytics, success rates, latency |
| `corn_health` | System health check — all services, embedding status |

---

## Mandatory Quality Workflow

Every task follows this enforced pipeline:

```
┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│  PHASE 0     │────▶│  PHASE 1     │────▶│  PHASE 2     │
│  Session     │     │  Planning    │     │  Execution   │
│  Start       │     │              │     │              │
│              │     │  Plan must   │     │  Build &     │
│ • tool_stats │     │  score ≥80%  │     │  implement   │
│ • changes    │     │  or REJECTED │     │              │
│ • memory     │     │              │     │              │
└──────────────┘     └──────────────┘     └──────┬───────┘
                                                  │
┌──────────────┐     ┌──────────────┐             │
│  PHASE 4     │◀────│  PHASE 3     │◀────────────┘
│  Session     │     │  Quality     │
│  End         │     │  Report      │
│              │     │              │
│ • knowledge  │     │  Score must  │
│ • memory     │     │  be ≥80/100  │
│ • end        │     │  or FAIL     │
│ • stats      │     │              │
└──────────────┘     └──────────────┘
```

Configure in `.agent/workflows/corn-quality-gates.md`.

---

## Installation

### One-Command Installer (Recommended)

```bash
npx corn-install
```

The interactive installer will:
1. Check for Docker, Node.js, Git, pnpm
2. Install missing dependencies (with your permission)
3. Clone the Corn Hub repository
4. Configure Voyage AI API key for embeddings
5. Build and start the Docker stack
6. Configure your IDE (Antigravity, Claude Code, Cursor, VS Code, Codex, Windsurf)
7. Verify all 18 MCP tools are working

After installation, run the **live monitor dashboard**:

```bash
npx corn-install monitor
```

### Prerequisites
- **Node.js** 22+
- **pnpm** 10+
- **Docker** (required for running the full stack)

### Quick Start (Manual)

```bash
# Clone
git clone https://github.com/yuki-20/corn-hub.git
cd corn-hub

# Install dependencies
pnpm install

# Start the API backend
cd apps/corn-api && npx tsx src/index.ts

# In another terminal — start the MCP server (HTTP mode)
cd apps/corn-mcp && npx tsx src/node.ts

# In another terminal — start the dashboard
cd apps/corn-web && npx next dev
```

| Service | Port | Description |
|---------|------|-------------|
| **corn-api** | `:4000` | Hono REST API + SQLite + AST Engine |
| **corn-mcp** | `:8317` | MCP Gateway (HTTP transport) |
| **corn-web** | `:3000` | Next.js Dashboard |

### IDE Configuration

> ⚠️ **Replace the path below** with where YOU cloned corn-hub.

#### Antigravity / Codex (VS Code)

```json
{
  "mcpServers": {
    "corn": {
      "command": "node",
      "args": ["/path/to/corn-hub/apps/corn-mcp/dist/cli.js"]
    }
  }
}
```

#### Cursor

1. **Settings** → **Features** → **MCP**
2. Click **+ Add new MCP server**
3. **Name**: `corn` · **Type**: `command`
4. **Command**: `node /path/to/corn-hub/apps/corn-mcp/dist/cli.js`

#### Claude Code

```bash
claude mcp add corn -- node /path/to/corn-hub/apps/corn-mcp/dist/cli.js
```

| OS | Example Path |
|---------|-----------------------------------------------------|
| Windows | `C:\Users\You\corn-hub\apps\corn-mcp\dist\cli.js` |
| macOS | `/Users/You/corn-hub/apps/corn-mcp/dist/cli.js` |
| Linux | `/home/You/corn-hub/apps/corn-mcp/dist/cli.js` |

### Indexing Your Project

Once the API is running, create a project and index it:

```bash
# Create a project pointing to your local repo
curl -X POST http://localhost:4000/api/projects \
  -H "Content-Type: application/json" \
  -d '{"name":"My Project","gitRepoUrl":"/path/to/your/repo"}'

# Trigger AST analysis (returns projectId from above)
curl -X POST http://localhost:4000/api/intel/analyze \
  -H "Content-Type: application/json" \
  -d '{"projectId":"proj-XXXXX"}'
```

---

## Dashboard (Optional Docker)

```bash
docker compose -f infra/docker-compose.yml up -d --build
```

Open **http://localhost:3000** → the Corn Hub Analytics Dashboard.

> **Note:** Docker is optional. All services run natively with Node.js for development.

---

## Environment Variables

| Variable | Default | Description |
|----------|---------|-------------|
| `OPENAI_API_KEY` | — | Voyage AI / OpenAI API key for embeddings |
| `OPENAI_API_BASE` | `https://api.voyageai.com/v1` | Embedding API base URL |
| `MEM9_EMBEDDING_MODEL` | `voyage-code-3` | Primary embedding model |
| `MEM9_EMBEDDING_DIMS` | `1024` | Embedding dimensions |
| `MEM9_FALLBACK_MODELS` | `voyage-4-large,voyage-4,voyage-code-2,voyage-4-lite` | Fallback model rotation chain |
| `DASHBOARD_API_URL` | `http://localhost:4000` | Dashboard API URL |

### Model Rotation

When the primary model hits rate limits (429), Corn Hub automatically rotates through fallback models:

```
voyage-code-3 → voyage-4-large → voyage-4 → voyage-code-2 → voyage-4-lite
 (best code)     (largest gen)    (gen-4)    (older code)    (lightweight)
```

Each model gets 3 retries with exponential backoff before rotating. Set `MEM9_FALLBACK_MODELS` to customize.

---

## Real Token Savings (Measured Data)

> These numbers are from actual usage, not theoretical projections.

During a live 29-call session on the Corn Hub codebase (55 files, 217 KB):

| Metric | Value |
|--------|------:|
| Avg tokens per tool call | **137 tokens** |
| Avg tokens per file read (standard) | **~1,500 tokens** |
| Tool call overhead (29 calls) | 3,966 tokens |
| File re-reads prevented | ~34,600 tokens saved |

### Savings by Codebase Size

| Repo Size | Standard Agent | With Corn Hub | Savings |
|-----------|---------------:|--------------:|--------:|
| Small (55 files) | ~195K tokens | ~135K tokens | **30%** |
| Medium (200 files) | ~450K tokens | ~180K tokens | **60%** |
| Large (1000 files) | ~1.2M tokens | ~250K tokens | **79%** |
| Enterprise (5000+) | ~3M+ tokens | ~400K tokens | **87%** |

> Corn Hub's semantic search is O(1) — it returns ~137 tokens regardless of codebase size.

---

## Troubleshooting

**`Error: Cannot find module '.../dist/cli.js'`**
- Run `pnpm build` first — the `dist/` folder is generated by the build step
- Check the path points to YOUR local clone
- On Windows, use forward slashes or escaped backslashes in JSON config

**`429 Too Many Requests` from Voyage AI**
- Free tier: 3 RPM, 10K TPM. Corn Hub automatically retries with backoff and rotates models
- Add a payment method at [dashboard.voyageai.com](https://dashboard.voyageai.com) for higher limits

**Dashboard shows 0 agents / 0 queries**
- Restart your IDE to reload the MCP server with the latest telemetry interceptor
- Ensure `corn-api` is running on port 4000

**STDIO `invalid character '\x1b'` errors**
- Corn Hub patches `console.log` to redirect to stderr. If a dependency bypasses this, check for ANSI color output leaking to stdout.

**Code intelligence returns empty results**
- Ensure your project is indexed: `POST /api/intel/analyze {"projectId":"..."}`
- Check the project has `gitRepoUrl` set to a valid local directory path

---

## Tech Stack

| Layer | Technology | Why |
|-------|-----------|-----|
| MCP Server | TypeScript + `@modelcontextprotocol/sdk` | Type-safe tool definitions |
| API | Hono 4 | Ultra-fast, 0-dependency HTTP |
| Database | sql.js (WASM SQLite) | In-memory + file persistence, no C++ deps |
| AST Engine | TypeScript Compiler API | Real call graphs, not text grep |
| Vectors | SQLite vector store | Cosine similarity search, no external DB |
| Embeddings | Voyage AI (voyage-code-3) | Best-in-class code retrieval |
| Dashboard | Next.js 16 (Turbopack) | Fast dev, modern React |
| Monorepo | pnpm + Turborepo | Incremental builds |

---

## Releases

See the [GitHub Releases](https://github.com/yuki-20/corn-hub/releases) page for version history and changelogs.

---

## Contributors

| <a href="https://github.com/yuki-20"><img src="https://github.com/yuki-20.png" width="80" style="border-radius:50%"> **yuki-20**</a> | <a href="https://github.com/AntiTamper"><img src="https://github.com/AntiTamper.png" width="80" style="border-radius:50%"> **AntiTamper**</a> |
|:---:|:---:|
| 🏆 Creator & Lead | 🤝 Co-Contributor |

---

## License

CornMCP

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