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Copy-paste examples: connect an AI agent to the Rein Agent Risk Scale self-check over MCP

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Last scanned: 10/10/2026
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/reinlayer/rein-examples
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "rein-examples": {
      "command": "node",
      "args": ["/path/to/rein-examples/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "<openai_api_key>"
      }
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/reinlayer/rein-examples and follow its README for install instructions.
Detected environment variables
OPENAI_API_KEY
Use cases

MCP Servers overview

# Rein Agent Risk Scale: MCP examples

Copy-paste examples that connect an AI agent to the **Rein Agent Risk Scale** self-check over MCP. The self-check gives an agent that can spend money an indicative Agent Risk Rating on an A–D scale (NR = not rated), from the controls around it: who is accountable, spend caps and where they are enforced, payee limits, a stop switch and who holds it, human escalation, monitoring, history and incidents.

**MCP endpoint** (streamable HTTP, no sign-in):

    https://rein-scale.mangowave-ad191d9c.eastus.azurecontainerapps.io/mcp

The endpoint has three tools:
- `self_check` scores a deployment from structured answers;
- `get_scale` returns the A–D scale (NR = not rated) and what each grade means;
- `explain_grade` says what a grade requires.

Scoring is fixed, published rules with no language model, so the same answers always give the same grade (methodology 0.3.1). Harness memory counts in your favour within your grade's band; it never moves the letter.

**Self-declared and unverified; not a credit rating.**

## Examples

Each example is one file of under 40 lines.

| file | framework | install (tested versions) |
|---|---|---|
| [`examples/plain_mcp.py`](examples/plain_mcp.py) | the `mcp` Python SDK, no LLM | `pip install "mcp==2.3.0"` |
| [`examples/openai_agents.py`](examples/openai_agents.py) | OpenAI Agents SDK | `pip install "openai-agents==0.23.1"` |
| [`examples/langgraph_agent.py`](examples/langgraph_agent.py) | LangChain / LangGraph with the MCP adapters | `pip install "langchain==1.4.3" "langchain-openai==1.6.7" "langchain-mcp-adapters==0.3.2"` |
| [`examples/crewai_agent.py`](examples/crewai_agent.py) | CrewAI | `pip install "crewai==1.15.23" "crewai-tools[mcp]==1.15.23"` |

The three agent examples use OpenAI by default (`export OPENAI_API_KEY=...`). Pass any model your framework accepts to `main()` to use another.

- **Tested:** every example was run against the live endpoint on 7 October 2026 at the versions above.
- **Watched weekly:** a check runs them against the latest framework releases, because releases rename things. `mcp` 2.x renamed its HTTP client, and it now yields two streams instead of three.

## Use it from any MCP client

```json
{
  "mcpServers": {
    "rein-agent-risk-scale": {
      "type": "http",
      "url": "https://rein-scale.mangowave-ad191d9c.eastus.azurecontainerapps.io/mcp"
    }
  }
}
```

There are docs written for agents at [`/skill.md`](https://rein-scale.mangowave-ad191d9c.eastus.azurecontainerapps.io/skill.md) and [`/llms.txt`](https://rein-scale.mangowave-ad191d9c.eastus.azurecontainerapps.io/llms.txt).

## What a self-check is, and is not

- **Indicative.** The grade comes from your own answers. It is self-declared and unverified, so the rated grade stays `NR` (not rated) until the controls are verified.
- **Explained.** The response lists the findings that most explain the grade and the steps that would raise it.
- **Private by default.** Answers and grades are stored under a pseudonymised record. A handle is published only if you set `publish_opt_in: true`. Never send secrets or personal data.
- **Not a credit rating,** not investment advice, and not an offer of credit.

## License

MIT. See [LICENSE](LICENSE).

What people ask about rein-examples

What is reinlayer/rein-examples?

+

reinlayer/rein-examples is mcp servers for the Claude AI ecosystem. Copy-paste examples: connect an AI agent to the Rein Agent Risk Scale self-check over MCP It has 0 GitHub stars and its last recorded update is dated 2026-10-09.

How do I install rein-examples?

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You can install rein-examples by cloning the repository (https://github.com/reinlayer/rein-examples) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is reinlayer/rein-examples safe to use?

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Our security agent has analyzed reinlayer/rein-examples and assigned a Trust Score of 87/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.

Who maintains reinlayer/rein-examples?

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reinlayer/rein-examples is maintained by reinlayer. The last recorded GitHub activity is dated 2026-10-09, with 0 open issues.

Are there alternatives to rein-examples?

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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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