# Datashift MCP Server

> Use this tool when you need to integrate human review and validation into AI workflows, enabling tasks to be submitted for evaluation and receiving decisions through MCP tools. It solves problems of accuracy and reliability by adding human oversight to AI-driven processes. The Datashift MCP Server takes in tasks and outputs reviewed decisions, making it ideal for use cases requiring hybrid human-AI collaboration.

Canonical page: https://skillsregistry.net/skills/datashift-io-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/datashift-io-mcp-server

## Description

Enables AI agents to submit tasks for human or AI review and receive decisions via MCP tools, adding human review checkpoints to workflows.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/kdgyeim401)
- **Repository:** <https://github.com/datashift-io/mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "datashift-io-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/datashift-io-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/datashift-io-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt