Start a monitoring scan for a project, sending prompts to configured LLMs and collecting responses. Returns a pending scan object. Requires project ID.
MIT
Destructive
650,545 tools. Updated 2026-10-14 08:59
"A server for making LLMs follow user prompts more strongly" matching MCP tools:
- Add monitoring prompts (questions for LLMs) to a brand monitoring project. Supports up to 50 prompts per request with optional tags, returning IDs for later scanning.MIT
- Lists competitor brands mentioned by LLMs in response to project prompts, showing the competitive landscape as seen by AI models.MIT
- Retrieve curated AI prompts tailored to a specific profession for use with ChatGPT, Claude, and other LLMs.MIT
- Follow an Instagram user or send a follow request for private accounts by visiting their profile and clicking the Follow button.Apache 2.0Destructive
- Browse Midjourney's public feed to discover other users' images and prompts. Use returned image URLs as style references for your own generations.MIT
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Matching MCP Connectors
Free copy-and-run ChatGPT prompts for online stores: 924 prompts, 43 categories + 10 tasks.
Crawls any website and generates a standards-compliant /llms.txt file and JSON-LD schema bundle.
- List all server-defined prompts, returning each prompt's name, description, and argument schema. Provides access to prompt details for clients without prompts/list MCP support.MIT
- Find past sessions related to a task description by matching session titles and original user prompts, enabling you to reuse prior work on the same topic.MIT
- Transform raw prompts into clearer, more detailed versions with better structure to improve LLM results. Enhances AI interactions by adding context and requirements.MIT
- Retrieve a structured catalog of all tools, resources, and prompts available on the server.MIT
- Request approval for an implementation plan before modifying multiple files or making significant changes. The plan summary is presented for user approval or rejection.MIT
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- Retrieve pending prompts from Telegram to access queued user instructions. Call at session start or when the user asks to check for new commands.MIT
- Search for prompts mentioning a specific brand across multiple LLMs, with filters for volume, keyword count, and prompt length.Apache 2.0
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- Analyze prompts in your codebase to identify user-facing prompts requiring security badges and internal prompts needing audit review.-
- Retrieves all available prompts from a CheckPoint MCP server, providing each prompt's name, description, and arguments.-
- Analyze A/B testing results to identify which psychological manipulation personas effectively prompt LLMs to fix code errors.MIT
- Read recent written reviews for a package, set language and limit, and follow the next page token to fetch more.AGPL 3.0
- Ask Amazon's AI shopping assistant Rufus in natural language to get structured product recommendations with follow-up questions for scene-based or open-ended sourcing.MIT