MCP For Claude Marketplace
Agent Self-Reflection & Sentiment Scanner

Agent Self-Reflection & Sentiment Scanner MCP Connector for Claude

A+

Quantify agent self-correction behavior and sentiment by scanning execution logs for specific error and success markers.

2 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

The Agent Self-Reflection & Sentiment Scanner MCP server provides a specialized engine for analyzing agent execution logs. It identifies deterministic self-correction markers by performing exact phrase matching for error recognition (e.g., 'I made a mistake') and success indicators (e.g., 'The task is complete'). By processing these logs, the server can calculate a self-correction frequency rate per execution loop and determine if an agent's current state is 'Correcting' or 'Proceeding'. Use analyze_sentiment to evaluate the emotional tone of log entries and detect_reflection to identify instances where the agent expresses internal thoughts or feelings.

sentiment-analysisself-reflectionagent-monitoringlog-analysiserror-detection

2 tools expose this connector's capabilities to your AI agent.

detect_reflection

Detect if a text contains self-reflective elements

analyze_sentiment

Analyze the sentiment of a given text

See how to talk to your AI agent using Agent Self-Reflection & Sentiment Scanner.

Analyze this log: 'I made a mistake in the previous step. Let me try again. The task is complete.'

The logs contain error recognition markers ('I made a mistake', 'Let me try again') and a success marker ('The task is complete'). The agent's status is Proceeding.

Is the following text positive or negative: 'I am very happy with the results of this execution.'

The sentiment analysis indicates that the text is positive.

Does this log show self-reflection: 'I am thinking about the best way to approach this problem.'

Yes, the text contains elements of self-reflection as it expresses internal thought processes.

The scanner uses exact character-for-character comparison to find predefined error recognition phrases and success markers within your provided execution logs.

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