Dlt Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Dlt Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<h1 align="center"> <strong>data load tool (dlt) — MCP Server</strong> </h1> <p align="center"> 🚀 Follow <a href="https://dlthub.com/docs/dlt-ecosystem/llm-tooling/llm-native-workflow">this guide</a> to create a dlt pipeline in 10mins with AI </p>
Large language models (LLMs) know a lot about the world, but nothing about your specific code and data.
The Model Context Protocol (MCP) server allows the LLM to retrieve up-to-date and correct information about your dlt pipelines, datasets, schema, etc. This significantly improves the development experience in AI-enabled IDEs (Copilot, Cursor, Continue, Claude Code, etc.)
The package manager uv is required to launch the MCP server.
Add this section to your MCP configuration file inside your IDE. Add your destination(s) in the extras dlt-mcp[...]
{
"name": "dlt",
"command": "uv",
"args": [
"run",
"--with",
"dlt-mcp[duckdb]",
"dlt-mcp",
],
}>[!NOTE] >The configuration file format varies slightly across IDEs
The dlt MCP server provides tools that allows the LLM to take actions:
dlt documentation using different modes (hybrid, full_text, or vector) to verify features and identify recommended patterns.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.