# Bindry

> Bindry — ai-bindry-bindry. Use this tool when you need to reuse and deploy AI instructions across multiple platforms, solving the problem of duplicated effort and inconsistent outputs. Bindry enables the seamless integration of pre-built Bindings and Stacks in any MCP client, streamlining workflows and improving efficiency. It accepts existing AI instructions as input and outputs reusable, deployable code, ideal for teams working with multiple MCP clients.

Canonical page: https://skillsregistry.net/skills/ai-bindry-bindry  
JSON: https://api.skillsregistry.net/v1/skills/ai-bindry-bindry

## Description

Reuse your team's AI instructions (Bindings and Stacks) from Bindry in any MCP client.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.2.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-22

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.bindry%2Fbindry)

## Use it

MCP endpoint published by the skill: `https://api.bindry.ai/api/mcp`

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": "ai-bindry-bindry"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-bindry-bindry` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-bindry-bindry/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