Datris — The First AI Agent-Native Data Platform

datris.ai · Try Hosted Free · Documentation · MCP Registry · PyPI

Ingest, validate, transform, store, and retrieve your data — whether you're an AI agent talking through MCP or a developer writing config. One platform for both.

Why Datris?

• Agent-native — Built-in MCP server with 35+ tools. Claude, Cursor, OpenClaw, and any MCP-compatible agent can operate pipelines through natural conversation
• Taps — AI-generated Python scripts that fetch data from external sources (APIs, web scraping, databases) and push it into pipelines. Describe what you want, Datris generates the script. Includes AI diagnosis, CRON scheduling, and credentials via Vault
• AI at every stage — AI data quality, AI transformations, AI schema generation, AI profiling, AI error explanation, natural language queries, RAG
• No vendor lock-in — 100% open-source infrastructure (MinIO, PostgreSQL, MongoDB, Kafka, Vault). Runs anywhere Docker does
• Configuration-driven — Define pipelines through JSON. No code required

Quick Start

git clone https://github.com/datris/datris-platform-oss.git
cd datris-platform-oss
cp .env.example .env       # Add your ANTHROPIC_API_KEY and/or OPENAI_API_KEY
docker compose up -d

UI: http://localhost:4200 · API: http://localhost:8080

Connect an AI Agent

Add to your MCP client config (Claude Desktop, Cursor, etc.):

{
  "mcpServers": {
    "datris": {
      "command": "uvx",
      "args": ["datris-mcp-server"],
      "env": {
        "PIPELINE_URL": "http://localhost:8080"
      }
    }
  }
}

CLI

brew tap datris/tap
brew install datris
datris ingest data.csv --dest postgres
datris ingest sales.csv --ai-validate "prices > 0" --ai-transform "convert dates to YYYY/MM/DD"
datris query "SELECT * FROM sales"
datris search "quarterly revenue" --store pgvector
datris tap create "Fetch S&P 500 daily prices from yfinance" --pipeline stocks
datris taps

What It Does

Source (File Upload / MinIO Event / Database Pull / Kafka)
  → Preprocessor (optional REST endpoint)
  → Data Quality (AI rules, header validation, schema validation)
  → Transformation (AI transformation, destination schema)
  → Destinations (in parallel):
      PostgreSQL, MongoDB, MinIO (Parquet/ORC), Kafka, ActiveMQ,
      REST Endpoint, Qdrant, Weaviate, Milvus, Chroma, pgvector
  → Notifications (ActiveMQ topic)

AI-Powered Features

Supported Formats

CSV, JSON, XML, Excel, PDF, Word, PowerPoint, HTML, email, EPUB, plain text, .zip/.tar/.gz archives

AI Providers

Anthropic Claude (Opus 4.6, Sonnet 4.6, Haiku) · OpenAI (GPT-5, GPT-4.1, o3) · Ollama (local models)

Architecture

Documentation

Full documentation at docs.datris.ai or locally at docs/.

License

AGPL-3.0