How do I use cerebro?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@cerebro compress the current prompt to a 50% rate and store it in the brain" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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cerebro

by Wendell-A

Overview Schema Related Servers Score Discussions

TypeScript

Local

Cérebro 2.0

Context optimization server for OpenCode. Compresses LLM prompts via LLMLingua-2, injects task protocols, and provides a 2nd Brain knowledge graph.

Architecture

┌─────────────────────────────────────────────────┐
│                  OpenCode                        │
│  ┌──────────────┐  ┌──────────────────────────┐ │
│  │ Plugin       │  │ MCP Client               │ │
│  │ (hooks)      │  │ (tools)                  │ │
│  └──────┬───────┘  └────────────┬─────────────┘ │
│         │                       │                │
└─────────┼───────────────────────┼────────────────┘
          │                       │
    ┌─────▼─────┐          ┌──────▼──────┐
    │ Compressor │          │ MCP Server  │
    │ LLMLingua-2│          │ + HTTP API  │
    └─────┬─────┘          └──────┬──────┘
          │                       │
    ┌─────▼───────────────────────▼──────┐
    │           @cerebro/core             │
    │  compressor · task-injector · brain │
    └────────────────────────────────────┘

Packages

Package	Description
`@cerebro/core`	Compression engine, task injector, brain engine, metrics
`@cerebro/mcp-server`	MCP stdio server + HTTP API for dashboard
`@cerebro/plugin`	OpenCode plugin (message compression + task injection)
`@cerebro/dashboard`	Vite + React + Tailwind dashboard UI

Related MCP server: ContextStream MCP Server

Quick Start

# Install dependencies
pnpm install

# Approve native builds (onnxruntime-node)
pnpm approve-builds

# Run tests
pnpm test

# Build all packages
pnpm -r build

# Start MCP server (stdio for OpenCode)
node packages/mcp-server/dist/index.js

# Start dashboard dev server
pnpm --filter @cerebro/dashboard dev

Configuration

Environment variables (set in opencode.json under environment):

Variable	Default	Description
`COMPRESSION_RATE`	`0.4`	Compression rate (0.05–1.0, lower = more compression)
`BRAIN_PATH`	`.context-brain`	Path to 2nd Brain knowledge base
`DASHBOARD_PORT`	`4321`	HTTP API port for dashboard
`ENABLE_TASK_INJECTION`	`true`	Enable task protocol injection
`PROTECTED_PATTERNS`	`code,json,errors,system`	Comma-separated protected block patterns

OpenCode Integration

Add to opencode.json in your project root:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "cerebro": {
      "type": "local",
      "command": ["node", "caminho/para/cerebro/packages/mcp-server/dist/index.js"],
      "environment": {
        "COMPRESSION_RATE": "0.4",
        "BRAIN_PATH": ".context-brain",
        "DASHBOARD_PORT": "4321",
        "ENABLE_TASK_INJECTION": "true"
      },
      "enabled": true
    }
  }
}

MCP Tools

`compress_prompt`

Compress text using LLMLingua-2 ONNX.

{ "text": "Your long prompt...", "rate": 0.4 }

`brain_resolve`

Query the 2nd Brain for a screen and its wiki-linked dependencies.

{ "screen": "dashboard-vendas", "depth": 1 }

`brain_index`

Index or update a screen in the knowledge graph.

{
  "id": "dashboard-vendas",
  "content": "---\ntitle: Dashboard Vendas\n---\n\n# Dashboard Vendas\n\nMetrics for the sales dashboard."
}

`brain_screens`

List all indexed screens. No parameters.

`cerebro_metrics`

Get compression metrics and token savings. No parameters.

`cerebro_config`

Get or set runtime configuration.

{ "key": "compressionRate", "value": 0.3 }

Dashboard

The dashboard runs on port 4321 and provides:

Métricas: Compression stats, token savings, recent events
2º Cérebro: Browse indexed screens and their wiki-links
Config: View and edit runtime configuration

pnpm --filter @cerebro/dashboard dev
# Open http://localhost:4321

Plugin Hooks

The OpenCode plugin provides three hooks:

Hook	Description
`experimental.chat.messages.transform`	Compresses old messages before sending to LLM
`experimental.chat.system.transform`	Injects task protocol + self-check into system prompt
`tool.execute.after`	Logs tool execution for dashboard visibility

Development

# Type check all packages
pnpm -r typecheck

# Run tests
pnpm test

# Watch mode
npx vitest

# Build dashboard
pnpm --filter @cerebro/dashboard build

Testing

66 tests across 6 suites:

packages/core/src/          task-injector.test.ts (18) · metrics.test.ts (5)
packages/mcp-server/src/    errors.test.ts (9) · rate-limiter.test.ts (7) · e2e.test.ts (10)
packages/plugin/src/        plugin.test.ts (8)

Run with: pnpm test or npx vitest run

License

MIT

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Not graded

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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