Agent Bridge Suite 🚀

Monorepo suite bridging Antigravity and Claude Code through persistent cross-IDE episodic memory (Native SQLite FTS5 + BM25 Ranking Engine) and multi-model adversarial peer review (Speculative Consensus).

📦 Suite Packages

Related MCP server: Memory MCP

🚀 Quick Start & Installation

Prerequisites

• Node.js >= 20.0.0

• pnpm >= 9.0.0

Clone & Build

git clone https://github.com/roedyrustam/agent-bridge-suite.git
cd agent-bridge-suite
pnpm install
pnpm build

🔌 Setup with AI Agents

1. Antigravity IDE / CLI

Link the plugins directly into your Antigravity environment:

agy plugin link ./plugins/agent-memory-sync
agy plugin link ./plugins/speculative-twin

2. Claude Code CLI

Register both MCP servers in your Claude Code configuration:

claude mcp add agent-memory-sync node ./plugins/agent-memory-sync/dist/index.js
claude mcp add speculative-twin node ./plugins/speculative-twin/dist/index.js

3. Standalone Terminal CLI (agent-bridge)

Interact with memory or run code audits directly from your terminal without opening an MCP client:

# Query memories using BM25 ranking
pnpm agent-bridge memory recall "prisma connection pool starvation"

# Inspect memory stats and tag distribution
pnpm agent-bridge memory stats

# Run adversarial code critique (returns exit code 1 on P0 issues)
pnpm agent-bridge twin critique ./src/auth.ts --context="Strict authentication middleware"

# Generate speculative alternative implementations across 3 paradigms
pnpm agent-bridge twin speculate "Bounded async worker pool with backpressure"

# Check active twin provider and capability mode
pnpm agent-bridge twin status

⚙️ Model Provider Configuration (Speculative Twin)

By default, speculative-twin operates 100% offline using high-precision static heuristics with zero token costs. To enable live frontier cross-model reviews, set any of the following environment variables:

# Option A: Anthropic Claude (default: claude-3-5-sonnet-20241022)
export ANTHROPIC_API_KEY="sk-ant-..."
export ANTHROPIC_MODEL="claude-3-7-sonnet-latest" # optional

# Option B: Google Gemini (default: gemini-2.5-flash)
export GEMINI_API_KEY="..."
export GEMINI_MODEL="gemini-2.5-flash" # optional

# Option C: OpenAI or Custom Local LLM (default: gpt-4o)
export OPENAI_API_KEY="sk-..."
export OPENAI_BASE_URL="http://localhost:11434/v1" # e.g. Ollama or vLLM
export OPENAI_MODEL="deepseek-r1" # optional

🧰 MCP Tools Reference

agent-memory-sync

• memory_recall: Query historical insights, debugging traps, and user preferences using BM25 semantic scoring.

• memory_record: Save a durable lesson, bug fix, or architecture rule (gotchas, architecture, user_preferences, performance).

• memory_list: List all stored insights with category and project scope filters.

• memory_stats: View telemetry metrics (total items, category breakdown, top tags, most recalled items).

• memory_export: Export knowledge base to Markdown or JSON format.

• memory_import: Import backup memories with skip or overwrite merge modes.

• memory_delete: Delete obsolete memories by ID.

speculative-twin

• twin_critique: Stress-test code against security flaws, hardcoded credentials, silent catch blocks, SQL injection, loose any casts, and race conditions.

• twin_speculate: Generate candidate implementations across 3 algorithmic archetypes (Defensive Functional, High-Throughput Streaming, Minimal Zero-Alloc).

• twin_synthesize: Merge two competing code drafts into a unified, hardened solution.

• twin_status: Inspect active provider and capabilities.

🧪 Testing & Validation

The test suite is powered by Vitest and covers both plugins:

# Run all unit tests across monorepo packages
pnpm test

# Run build
pnpm build

✓ test/store.test.ts (7 tests)
✓ test/sqlite-store.test.ts (8 tests)
✓ test/engine.test.ts (10 tests)
Test Files  3 passed (3)
Tests       25 passed (25)

🤝 Contributing

Contributions, issues, and feature requests are welcome! Please feel free to check the issues page.

1. Fork the Project

2. Create your Feature Branch (git checkout -b feature/AmazingFeature)

3. Commit your Changes (git commit -m 'feat: Add some AmazingFeature')

4. Push to the Branch (git push origin feature/AmazingFeature)

5. Open a Pull Request

📄 License

Distributed under the MIT License. See LICENSE for more information.