Is the agentburn MCP server actively maintained?

The agentburn MCP server was last committed 29d ago and has 2 contributors. Issue health: 0% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

agentburn MCP Server

Name: Socialpranker/agentburn
Rating: 3.2 (1 reviews)
Author: Socialpranker

Socialpranker/agentburn

Score: 55.8 Rank #8954 Monitoring

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Which 5-hour window took you out — and where the money goes. Local profiler for Claude Code, OpenClaw & Hermes Agent: usage windows, burn by source (cron/chats/subagents), the overnight bill, why it burns (loops, retries, idle wake-ups), ready config fixes. Zero deps, nothing leaves your machine.

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claude mcp add agentrank -- npx -y agentrank-mcp-server

Overview

Socialpranker/agentburn is a Python tool licensed under MIT. Which 5-hour window took you out — and where the money goes. Local profiler for Claude Code, OpenClaw & Hermes Agent: usage windows, burn by source (cron/chats/subagents), the overnight bill, why it burns (loops, retries, idle wake-ups), ready config fixes. Zero deps, nothing leaves your machine. Topics: ai-agents, claude-code, cli, cost-tracking, hermes-agent, llm, mcp, observability, openclaw, profiler, python, token-usage, rate-limits, usage-limits.

Ranked #8954 out of 24846 indexed tools.

Ecosystem

Python MIT 124 pypi/wk

ai-agentsclaude-codeclicost-trackinghermes-agentllmmcpobservabilityopenclawprofilerpythontoken-usagerate-limitsusage-limits

Score Breakdown

Stars 15% 112

112 stars → growing community

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 0%

0/5 issues closed → many open issues

Contributors 10% 2

2 contributors → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads 13% 124/wk

124 weekly installs → early adoption

Forks 3

Description Detailed

License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Issue Health high impact

You have 5 open vs 0 closed issues — triaging stale issues improves health

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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Markdown

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HTML

<a href="https://agentrank-ai.com/tool/Socialpranker--agentburn/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/Socialpranker--agentburn" alt="AgentRank"></a>

Embed Widget docs →

HTML

<script src="https://agentrank-ai.com/embed.js" data-tool="Socialpranker/agentburn"></script>

Details

Stars: 112
Forks: 3
Open Issues: 5
Closed Issues: 0
Contributors: 2
Dependents: —
Language: Python
License: MIT
Last Commit: 29d ago

Matched Queries

topic:mcp

From the README

<div align="center">

<br>

<a href="https://pypi.org/project/agentburn/"></a>

<a href="../../actions/workflows/tests.yml"></a>
<a href="LICENSE"></a>

<br><br>

<br>

**[Claude Code](#supported-agents) · [Codex CLI](#supported-agents) · [Gemini CLI](#supported-agents) · [opencode](#supported-agents) · [OpenClaw](#supported-agents) · [Hermes Agent](#supported-agents)** — one normalized core, local, read-only, zero dependencies

```
uvx agentburn
```

**[▶ &nbsp;Try it in your browser — no install](https://socialpranker.github.io/agentburn/)**

</div>

---

## You didn't run out on your average day

You ran out inside **one window**. On this machine that window was **5.4× the median one** — same person, same week, same subscription.

Your assistant's own logs already know which window it was and what filled it. Nothing else on your machine does: the built-in counter shows a total, your invoice shows a total, and neither says *which five hours took you out.*

```
⏳ agentburn limits — cl

Read full README on GitHub →