# stele-mcp-connector

> stele-mcp-connector — stele-dev-stele-mcp-connector. Use this tool when you need to integrate your AI agent with a shared project memory, enabling persistent storage of decisions and tasks across sessions and clients. It solves problems of data loss and inconsistency by providing a unified repository, accessible via git, for project information. The stele-mcp-connector takes in AI agent inputs and outputs synchronized project data, making it ideal for collaborative and multi-session projects.

Canonical page: https://skillsregistry.net/skills/stele-dev-stele-mcp-connector  
JSON: https://api.skillsregistry.net/v1/skills/stele-dev-stele-mcp-connector

## Description

Connect your AI agent to Stele — shared project memory, decisions, and tasks that persist across sessions and clients.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Stele-Dev/stele-mcp-connector)

## 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": "stele-dev-stele-mcp-connector"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/stele-dev-stele-mcp-connector` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/stele-dev-stele-mcp-connector/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