Agent Self-Reflection & Sentiment Scanner Connector for AI agents.
2 live capabilities
Monitor self-correction frequency and log sentiment patterns.
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Why people use Agent Self-Reflection & Sentiment Scanner
Agent Self-Reflection & Sentiment Scanner for agent log observability
This MCP automates that search. It scans your logs for specific markers and gives you a clear metric on how often your agent is correcting itself.
What Vinkius changes
You get measurable metrics on agent reliability instead of just reading raw text.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Detecting infinite loops in agentic workflows
An engineer notices an agent is stuck; they use the MCP to see if the self-correction frequency has spiked.
- Real-world use case 02
Measuring prompt impact on error recovery
After updating a system prompt, a developer confirms the agent is reasoning more effectively through log analysis.
- Real-world use case 03
Monitoring production agent stability
An Ops engineer uses sentiment checks to alert when logs show high levels of error-related instability.
Complete set · 2capabilities
The complete Agent Self-Reflection & Sentiment Scanner capability set.
These are the exact actions your AI can choose when you ask it to work with Agent Self-Reflection & Sentiment Scanner.
01—02
2 capabilities in this set.
Part of 2 available through Agent Self-Reflection & Sentiment Scanner.
- 01 Capability
Analyze sentiment
Checks the emotional tone of a text string. It helps you spot when log entries become unstable.
- 02 Capability
Detect reflection
Scans text to find where an agent is expressing internal thoughts or reasoning.
Set up in minutes
One URL. Then ask Agent Self-Reflection & Sentiment Scanner to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Agent Self-Reflection & Sentiment Scanner 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_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Agent Self-Reflection & Sentiment Scanner for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner URL.
- Step 03
Save and start
Save the connection and enable Agent Self-Reflection & Sentiment Scanner in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-self-reflection-sentiment-scanner-alternative": {
"url": "https://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner
Open Agent mode in chat and ask: "Using Agent Self-Reflection & Sentiment Scanner, help me...". 2 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-self-reflection-sentiment-scanner-alternative": {
"url": "https://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner
Ask Copilot: "Using Agent Self-Reflection & Sentiment Scanner, help me...". 2 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-self-reflection-sentiment-scanner-alternative": {
"url": "https://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner
Open Cascade and ask: "Using Agent Self-Reflection & Sentiment Scanner, help me...". 2 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-self-reflection-sentiment-scanner-alternative": {
"url": "https://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner
Ask Cline: "Using Agent Self-Reflection & Sentiment Scanner, help me...". 2 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add agent-self-reflection-sentiment-scanner-alternative --transport http "https://edge.vinkius.com/vk_preview_F2yFzx4CchXScg2i4EwfRYqrArVJ0UEEfstzE52Z/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 Agent Self-Reflection & Sentiment Scanner
Ask Claude: "Using Agent Self-Reflection & Sentiment Scanner, show me...". 2 tools are ready
Where the request belongs
Work Agent Self-Reflection & Sentiment Scanner can move forward.
LLM Ops engineers and AI developers who need to monitor autonomous agent performance and stability in production.
LLM Ops Engineer
Monitoring long-running agent loops for error patterns and stability.
Testing if new prompts improve self-correction behavior during development.
Software Architect
Building observability layers for complex agentic workflows.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
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Quantify agent self-correction behavior and sentiment by scanning execution logs for specific error and success markers.
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Chattermill
Analyze customer feedback and sentiment via Chattermill. track AI-powered themes, monitor NPS and CSAT, and unify feedback from every channel directly from any AI agent.
Chainlit
Empower your AI agents to audit chat threads, analyze model steps, and track LLM observability metrics securely.
Bring your own AI
Change the model, client or framework. Keep Agent Self-Reflection & Sentiment Scanner 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 Agent Self-Reflection & Sentiment Scanner.
The practical details behind the request, access and result.
How can I track agent errors with Agent Self-Reflection & Sentiment Scanner?
It scans your execution logs for specific phrases like 'I made a mistake' to quantify error rates automatically.
Can Agent Self-Reflection & Sentiment Scanner help with monitoring agent loops?
Yes, it identifies if an agent is stuck in a 'correcting' state by tracking self-correction frequency.
Is Agent Self-Reflection & Sentiment Scanner useful for measuring prompt effectiveness?
It allows you to see if new prompts increase the rate of successful task completions or improve reasoning detection.
How does Agent Self-Reflection & Sentiment Scanner handle log sentiment?
It analyzes the tone of your logs to help you spot instability in agentic workflows before they fail completely.
Can I use Agent Self-Reflection & Sentiment Scanner with Claude or Cursor?
Yes, any MCP-compatible client like Claude, Cursor, or Windsurf can use this to analyze your logs.
How does the scanner identify self-correction?
The scanner uses exact character-for-character comparison to find predefined error recognition phrases and success markers within your provided execution logs.
Can I use this to monitor multiple agents?
Yes, you can pass the raw log text from any agent execution loop into the capabilities to analyze patterns across different agents and sessions.
What is the difference between `analyze_sentiment` and `detect_reflection`?
analyze_sentiment evaluates whether text is positive, negative, or neutral, while detect_reflection specifically looks for markers of internal thought or self-awareness.
One connection away
Give your agent a direct line to Agent Self-Reflection & Sentiment Scanner.
Connect Agent Self-Reflection & Sentiment Scanner once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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