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Lightning-fast data access platform designed specifically for AI agents
From the repo.
A lightning-fast data access platform for AI Agents that leverages graph-enhanced retrieval (LightRAG) to make any data source instantly accessible.
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# Clone and install
git clone https://github.com/tryprotege/almanac.git
cd almanac
pnpm install
# Start everything (one command)
pnpm start
Open http://localhost:5173 to access the UI.
First-time setup:
Comprehensive guides and tutorials are available in the docs directory:
External APIs → MCP Servers → Almanac
↓
[Syncing & Indexing]
↓
┌─────────────────────┐
│ Databases │
│ - MongoDB (docs) │
│ - Qdrant (vectors) │
│ - Memgraph (graph) │
│ - Redis (cache) │
└─────────────────────┘
↓
[LightRAG Query Engine]
↓
Results
almanac/
├── packages/
│ ├── client/ # React + Vite frontend
│ ├── server/ # Express.js backend
│ ├── shared-util/ # Shared utilities
│ ├── indexing-engine/ # LightRAG implementation
│ └── benchmark/ # Performance testing
├── docs/ # Full documentation
└── docker-compose.yml # Infrastructure services
| Service | Port | Purpose |
|---|---|---|
| Frontend | 5173 | Web UI |
| Backend | 3000 | REST API |
| MongoDB | 27017 | Document database |
| Qdrant | 6333, 6334 | Vector database |
| Memgraph | 7687, 7444 | Graph database |
| Redis | 6379 | Cache |
# Start all services
pnpm start # Infrastructure + apps locally
# Development
pnpm dev # Run client + server in dev mode
pnpm build # Build all packages
pnpm test # Run all tests
pnpm type-check # Type check all packages
# Docker options
pnpm run docker:infra # Start databases only
pnpm run docker:dev # Full Docker development mode
pnpm run docker:prod # Full Docker production mode
pnpm run docker:down # Stop all services
The scripts/syncAndBenchmark.sh script automates the complete workflow of wiping data, starting services, registering MCP servers, syncing records, indexing data, and running benchmarks.
Basic Usage:
./scripts/syncAndBenchmark.sh
Options:
--mcp-servers=<server1,server2> - Specify which MCP servers to enable (comma-separated). Available servers: notion, github, fathom, slack. If not specified, all servers are enabled.--skip-benchmark - Skip running benchmark tests--skip-index-vector - Skip vector indexing--skip-index-graph - Skip graph indexingExamples:
# Enable only GitHub and Notion servers
./scripts/syncAndBenchmark.sh --mcp-servers=github,notion
# Skip benchmark tests but run full indexing
./scripts/syncAndBenchmark.sh --skip-benchmark
# Enable only Slack, skip vector indexing
./scripts/syncAndBenchmark.sh --mcp-servers=slack --skip-index-vector
# Enable all servers, skip both indexing steps
./scripts/syncAndBenchmark.sh --skip-index-vector --skip-index-graph
# Full workflow with only GitHub and Fathom
./scripts/syncAndBenchmark.sh --mcp-servers=github,fathom
What the script does:
Client Package:
cd packages/client
pnpm dev # Start Vite dev server
pnpm build # Build for production
pnpm preview # Preview production build
Server Package:
cd packages/server
pnpm dev # Start server with hot reload
pnpm build # Build TypeScript
pnpm start # Start production server
pnpm test # Run tests
bolt://localhost:7687mongodb://admin:admin123@localhost:27017The easiest way to configure Almanac is through the web interface:
pnpm startAlternatively, you can manually edit the .env file:
cp packages/server/.env.example packages/server/.env
# Edit packages/server/.env with your settings
Required Settings:
LLM_API_KEY - Your LLM provider API keyOptional Settings:
RERANKER_ENABLED - Enable reranking for better search resultsENCRYPTION_KEY - Auto-generated if not providedSee packages/server/.env.example for all available options.
Almanac exposes an MCP (Model Context Protocol) server that allows AI clients to directly access your indexed data:
Once connected, your AI assistant can search across all your data sources using natural language queries.
This project is licensed under the terms specified in the LICENSE file.
Built for developers, by developers. Open source and production-ready.
Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.
Tool
OS
Config file: ~/.cursor/mcp.json
{
"mcpServers": {
"mcp-server": {
"url": "{MCP_ENDPOINT_URL}"
}
}
}Paste into mcpServers in the config file. Restart Cursor after saving.
If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.