---
title: ToolRouter — Agent Use Case Guide
description: Step-by-step guide for completing a task with a specific AI agent using ToolRouter.
url: https://toolrouter.com/tools/similar-movies/use-cases/find-your-next-movie-after-a-favorite/openclaw
---
# How to Find Similar Movies with OpenClaw

OpenClaw is a good fit when the same recommendation pattern will be reused across many seeds or recurring runs. Use `find_similar` to keep the schema stable while cycling through many favorite titles.

## Setup

openclaw mcp add toolrouter -- npx -y toolrouter-mcp

## Steps

1. Connect ToolRouter in OpenClaw: openclaw mcp add toolrouter -- npx -y toolrouter-mcp
2. Define the seed title, output size, and any permanent ranking rules such as minimum score or no franchise repeats.
3. Run `similar-movies.find_similar` and keep the shortlist fields normalized across calls.
4. Review the ranked result set and rerun with tighter filters only when the shortlist is still too broad.
5. Store the normalized output for reuse in editorial, automation, or personalization flows.

## Example Prompt

```
Use similar-movies to find movies like Inception, exclude same-collection results, and keep the output normalized so I can reuse the shortlist later.
```

## Tips

- Normalize the shortlist from the first run if you plan to compare seeds later.
- Use the same `min_vote_average` threshold across repeated runs to keep quality consistent.
- This works best for targeted recommendation batches rather than open-ended browsing.
