# Agent Error Recovery Rate Calculator MCP for AI Agents MCP

> Agent Error Recovery Rate Calculator parses your execution logs to find exactly how often your agent recovers from a failure. It identifies error signatures like timeouts or syntax errors and calculates recovery rates, helping you measure the true resilience of your automated workflows.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_mxorvHJdMuypEudO4shEOhJsee7lRGYjbFo9FKjU/mcp
- **Tags:** mcp, logs, error-analysis, recovery-rate, debugging

## Description

The Agent Error Recovery Rate Calculator lets you stop manually scanning through lines of text to see if your agent is actually working. When you're running complex workflows, seeing a 'failed' message isn't enough; you need to know if that failure was a dead end or just a temporary hiccup that the following step fixed. This MCP looks for specific markers in your logs and does the math for you. It pulls out error types like timeouts or syntax issues so you can see exactly what is breaking your processes. You don't have to build your own parser or write custom scripts to track these metrics. By connecting through Vinkius, you get a direct way to audit your agentic performance without leaving your preferred environment. It turns raw, messy logs into clear, actionable statistics about how often your agent successfully recovers from transient errors.

## Tools

### analyze_logs
It scans your logs to find the ratio of failures that eventually succeed. It also pulls out specific error signatures like SyntaxError or Timeout.

## Prompt Examples

**Prompt:** 
```
Check my recovery rate for these logs: 'SUCCESS: tool_a', 'PREVIOUSLY FAILED: tool_b - Timeout', 'SUCCESS: tool_c'.
```

**Response:** 
```
Your recovery rate is **100.0%**. 

There was one recorded failure, and it was immediately followed by a successful execution.
```

**Prompt:** 
```
What are the error signatures in this log: 'PREVIOUSLY FAILED: tool_x - SyntaxError', 'PREMS: tool_y - Timeout'.
```

**Response:** 
```
I found the following error signatures:

* **SyntaxError**: 1 occurrence
* **Timeout**: 1 occurrence
```

**Prompt:** 
```
How many failures recovered in this batch?
```

**Response:** 
```
In the provided log snippet, there were **2** instances where a failure was followed by a successful tool call.
```

## Capabilities

### Calculate recovery percentages
Find the exact ratio of failed tool calls that are followed by a successful execution.

### Extract error signatures
Automatically pull specific error types like SyntaxError or Timeout from your log strings.

### Identify failure patterns
See which errors are transient and which ones consistently lead to workflow termination.

### Audit execution logs
Scan through large volumes of success and failure markers to generate performance stats.

### Monitor workflow resilience
Quantify how well your agentic processes handle unexpected errors during runtime.

## Use Cases

### Debugging a loop of failures
An engineer notices an agent is stuck and uses the MCP to see if it's actually recovering or just failing repeatedly.

### Monitoring new agent deployments
After pushing a new version, you check the recovery rate to ensure transient errors aren't causing permanent breaks.

### Auditing long-running workflows
You run a massive batch of tasks and use the tool to find which specific error signatures are most common across the set.

### Comparing prompt versions
You compare the recovery rates of two different prompts to see which one handles tool failures more gracefully.

## Benefits

- Stop manual log counting by using analyze_logs to automate the math.
- Spot recurring timeouts immediately through automated error signature extraction.
- Measure actual workflow resilience by tracking how often failures lead to successes.
- Identify specific syntax errors causing breaks without reading every line of text.
- Quantify agent stability with clear recovery rate statistics.

## How It Works

The bottom line is you stop guessing how resilient your workflows are.

1. Provide the MCP with access to your execution or tool logs.
2. The tool parses the success and failure markers within the text.
3. You receive a detailed breakdown of recovery rates and identified error signatures.

## Frequently Asked Questions

**How does Agent Error Recovery Rate Calculator help with debugging?**
It automates the math of finding how often your agent recovers from errors. Instead of counting lines, you get instant stats on recovery frequency and error types.

**Can I use Agent Error Recovery Rate Calculator to find specific errors?**
Yes. It extracts exact signatures like SyntaxError or Timeout so you can see exactly which issues are recurring in your logs.

**Does Agent Error Recovery Rate Calculator work with Claude or Cursor?**
Yes, it works with any MCP-compatible client including Claude, Cursor, and Windsurf.

**What kind of logs does Agent Error Recovery Rate Calculator need?**
It needs logs that use the 'SUCCESS:' and 'PREVIOUSLY FAILED:' format to accurately calculate your recovery metrics.

**Will Agent Error Recovery Rate Calculator show me my success rate?**
It specifically focuses on the recovery rate, which is how often a failure is followed by a success, helping you measure resilience.

**What log format does the tool require?**
The `analyze_logs` tool expects logs in two specific formats: 'SUCCESS: ' for successful operations and 'PREVIOUSLY FAILED:  - ' to capture failures and their error signatures.

**How is the recovery rate calculated?**
The recovery rate is computed by identifying every instance where a 'SUCCESS' entry immediately follows a 'PREVIOUSLY FAILED' entry, then dividing that count by the total number of failures.

**Can it detect specific error types?**
Yes, the tool performs string matching to extract and count exact error signatures like 'Timeout', 'InvalidAPIKey', or 'SyntaxError' from your logs.