Prompt Resistance Scorer Connector for AI agents.
3 live capabilities
Quantify system prompt robustness against instruction injection
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Why people use Prompt Resistance Scorer
Prompt System Override Resistance Scorer for prompt injection security
With this MCP, you replace guesswork with math. You can instantly see if your new instructions have introduced 'leaks' that make your agent easy to manipulate. You get an actual security score instead of just a feeling.
What Vinkius changes
You get a measurable score for how hard your prompts are to manipulate.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Hardening a customer-facing bot
An engineer uses locate_vulnerable_segments to find where 'maybe' or 'sometimes' is weakening their core rules.
- Real-world use case 02
Verifying prompt updates
A developer runs calculate_resistance_ratio after a rewrite and finds the ratio dropped from 0.
- Real-world use case 03
Setting deployment thresholds
An automated pipeline uses determine_boundary_score to block any prompt that falls below a safety score of 0.
Complete set · 3capabilities
The complete Prompt Resistance Scorer capability set.
These are the exact actions your AI can choose when you ask it to work with Prompt Resistance Scorer.
01—03
3 capabilities in this set.
Part of 3 available through Prompt Resistance Scorer.
- 01 Capability
Calculate resistance ratio
Compares directive keywords against permissive ones to find instruction leaks. It shows exactly how much your commands are being diluted.
- 02 Capability
Determine boundary score
Turns a raw resistance ratio into a standardized security metric. This makes it easy to set hard thresholds for prompt deployment.
- 03 Capability
Locate vulnerable segments
Pinpoints specific parts of your prompt that lack enough command density. It highlights the exact areas where an attacker could succeed.
Set up in minutes
One URL. Then ask Prompt Resistance Scorer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Prompt Resistance Scorer from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Prompt Resistance Scorer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Prompt Resistance Scorer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Prompt Resistance Scorer URL.
- Step 03
Save and start
Save the connection and enable Prompt Resistance Scorer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-system-override-resistance-scorer": {
"url": "https://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Prompt Resistance Scorer
Open Agent mode in chat and ask: "Using Prompt Resistance Scorer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-system-override-resistance-scorer": {
"url": "https://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Prompt Resistance Scorer
Ask Copilot: "Using Prompt Resistance Scorer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-system-override-resistance-scorer": {
"url": "https://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Prompt Resistance Scorer
Open Cascade and ask: "Using Prompt Resistance Scorer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-system-override-resistance-scorer": {
"url": "https://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Prompt Resistance Scorer
Ask Cline: "Using Prompt Resistance Scorer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add prompt-system-override-resistance-scorer --transport http "https://edge.vinkius.com/vk_preview_3YrtTuRCxmV5HM166voZTOyHOTbBi5cCHn25jGrb/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Prompt Resistance Scorer
Ask Claude: "Using Prompt Resistance Scorer, show me...". 3 tools are ready
Where the request belongs
Work Prompt Resistance Scorer can move forward.
This is for the engineers who cannot afford to have their LLM applications hijacked by prompt injection.
Prompt Engineer
Auditing new instructions for injection risks before they go live.
AI Security Researcher
Quantifying the robustness of large-scale prompt libraries across different models.
LLM Developer
Testing if updates to system prompts introduce new vulnerabilities or instruction drift.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Prompt Injection Pattern Scanner
Scans user-supplied text for structural patterns associated with prompt-injection attempts.
Prompt Injection Detection Engine
Scans user inputs and retrieved documents for prompt injection attacks using static pattern matching.
System Prompt Leakage Detector
Detects verbatim leaks of system prompts within agent outputs using LCS algorithms.
Aporia
Monitor AI models and validate LLM interactions with guardrails directly from your AI agent to ensure safety and observability.
Braintrust
Automate AI evaluations with Braintrust. organize projects, test model datasets, run benchmarks, and manage prompts via any AI agent.
Bring your own AI
Change the model, client or framework. Keep Prompt Resistance Scorer connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Prompt Resistance Scorer.
The practical details behind the request, access and result.
How can I use Prompt System Override Resistance Scorer to prevent prompt injection?
You use it to find the linguistic gaps where an attacker could bypass your rules. By identifying permissive language, you can rewrite instructions to be more robust.
Can Prompt System Override Resistance Scorer help with instruction drift?
Yes. It identifies segments of your prompt that lack enough command density, which is exactly where instructions start to drift or fail.
Does Prompt System Override Resistance Scorer work with any LLM?
It works with any text-based system prompt. Since it analyzes the linguistic structure of your instructions, the underlying model does not matter.
How do I know if my Prompt System Override Resistance Scorer score is good?
A higher ratio and boundary score indicate a more secure prompt. You should set a threshold based on your specific security needs for your application.
Is Prompt System Override Resistance Scorer easy to automate?
Absolutely. You can integrate it into your CI/CD pipeline to automatically audit every version of your system prompts before they are deployed.
How does the resistance ratio work?
The calculate_resistance_ratio capability counts exact occurrences of directive keywords (MUST, NEVER, ONLY, ALWAYS) and divides them by the count of permissive keywords (maybe, usually, sometimes).
What is a 'vulnerable segment'?
A vulnerable segment is a portion of text identified by locate_vulnerable_segments where the concentration of directive keywords is significantly lower than the overall prompt average, indicating a potential area for instruction override.
Can I use this to prevent prompt injection?
Yes, by using determine_boundary_score, you can quantify the risk level of your prompt and identify if it falls into a 'Critical' or 'Vulnerable' tier based on its resistance to manipulation.
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