# DataForge Semantic MCP Server

> Use this tool when you need to integrate AI agents with DataForge metadata, streamlining access to projects, versions, measures, and dimensions through automated normalization and caching. It solves problems of data inconsistency and slow metadata retrieval, providing a standardized interface for AI agents to interact with the DataForge Product API. The tool accepts MCP protocol inputs and outputs normalized metadata, ideal for use cases requiring efficient and standardized data exchange.

Canonical page: https://skillsregistry.net/skills/sgromych-dataforge-mcp-gateway  
JSON: https://api.skillsregistry.net/v1/skills/sgromych-dataforge-mcp-gateway

## Description

Provides a semantic gateway for AI agents to interact with the DataForge Product API, enabling the retrieval of projects, versions, measures, and dimensions. It features automated normalization and file-based caching to streamline access to DataForge metadata through the MCP protocol.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tqgmqyelk1)
- **Repository:** <https://github.com/SGromych/dataforge-mcp-gateway>

## 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": "sgromych-dataforge-mcp-gateway"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sgromych-dataforge-mcp-gateway` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sgromych-dataforge-mcp-gateway/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