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datris-mcp-server
Advanced tools
MCP server for AI-driven data pipeline operations — ingest, validate, transform, analyze, and query data. Tools covering ETL, AI data quality, vector search, PostgreSQL, MongoDB, Snowflake, Databricks, Kafka, S3/MinIO, HashiCorp Vault, Qdrant, Weaviate, Milvus, Chroma, pgvector.
MCP (Model Context Protocol) server for the Datris AI Agent-Native Data Platform. Enables AI agents (Claude Desktop, Claude Code, Cursor, and custom frameworks) to natively interact with the platform — discover data, create pipelines, upload files, monitor jobs, search vector databases, query structured data, and answer questions with AI.
pip install datris-mcp-server
DATRIS_API_URL=http://localhost:8080 datris-mcp-server
Or run directly:
DATRIS_API_URL=http://localhost:8080 python server.py
DATRIS_API_URL=http://localhost:8080 datris-mcp-server --sse --port 3000
The MCP server starts automatically with docker compose up in SSE mode on port 3000.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"datris": {
"command": "datris-mcp-server",
"env": {
"DATRIS_API_URL": "http://localhost:8080"
}
}
}
}
Add to .mcp.json in your project root:
{
"mcpServers": {
"datris": {
"command": "datris-mcp-server",
"env": {
"DATRIS_API_URL": "http://localhost:8080"
}
}
}
}
| Variable | Default | Description |
|---|---|---|
DATRIS_API_URL | http://localhost:8080 | Datris REST API server URL |
REQUIRE_API_KEY | false | Reject SSE/HTTP sessions that connect without x-api-key |
There is no server-side API key. Each connecting agent authenticates per session by sending an x-api-key header; mcp-server forwards that key as-is to the Datris REST API on every tool call. The Datris REST API validates against oss/api-keys Vault secret (single-tenant) or api-key-mappings (multi-tenant). Manage keys in the Configuration UI's Secrets tab.
30+ tools across these categories:
See the full documentation at docs.datris.ai/mcp-server.
Apache 2.0
FAQs
MCP server for AI-driven data pipeline operations — ingest, validate, transform, analyze, and query data. Tools covering ETL, AI data quality, vector search, PostgreSQL, MongoDB, Snowflake, Databricks, Kafka, S3/MinIO, HashiCorp Vault, Qdrant, Weaviate, Milvus, Chroma, pgvector.
We found that datris-mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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