agentburn

Local profiler: which usage window took you out, and where your agent's money goes

Connector by Socialpranker · GitHub account verified by the MCP Registry

IndexedMITLocal (stdio)★ 113

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Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/socialpranker-agentburn

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Local profiler: which usage window took you out, and where your agent's money goes

Use cases: monitoring-observability

Reviews

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Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools: 0 read · 1 write · 0 delete · 5 not yet classified
Secrets: None asked for
Install scripts: Not scanned yet
Runs as: Python package

Tools by what they do 6

Read from the source code; the running server may list different tools.

Write 1 · Create, change, send or run things.

burn_commits

Not yet classified 5 · We could not tell from the name and description.

burn_card
burn_context
burn_limits
burn_report
burn_why

Files it touches

Any path the agent passes to its tools

Tools (6)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

burn_card
Anonymized shareable burn summary (plain text, safe to post).
burn_commits
What each git commit cost, in weighted tokens: sessions joined to the repositories they ran in (read-only git log). Costliest commits, median per repository. Returns JSON.
burn_context
The price of long contexts on this machine: share of the usage window spent at each context size, what a /clear at 100k/150k/200k/300k would have saved, the longest sessions, usage by effort level, and what each skill costs per load (measured from context growth). Returns JSON.
burn_limits
For subscription plans, where the invoice is fixed and what runs out is the usage window: how full the peak rolling 5-hour window got, how it compares with a typical one, what filled it (model, source, cache reads vs output). Weighted by published price ratios; no provider limit formula is assumed. Returns JSON.
burn_report
Where this machine's AI agent burns money: totals, monthly pace, breakdown by source (cron/heartbeat/gateways/subagents/cli), models, overnight window, fixed overhead per call, recommendations. Returns JSON.
burn_why
Behavioral forensics from the agent's own records: functions called (with error counts), re-read loops, retry storms, idle heartbeats, money burned in failed runs, plus what-to-change observations. Returns JSON.

Signals

Stars: 113
Forks: 3
Open issues: 2
Contributors: 2
Weekly downloads: 99
Last commit: Oct 19, 2026 (11 days ago)
Last release: Sep 6, 2026 (1 month ago)
Last package publish: Sep 6, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name: io.github.Socialpranker/agentburn
Version: 0.14.0
Auth: No auth
Packages: pypi agentburn
License: MIT
Repository: github.com/Socialpranker/agentburn
Website: github.com/Socialpranker/agentburn
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: Official MCP Registry github-graphql

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Cite this page

agentburn MCP server. Agent Mart. https://agentmart.dev/connectors/socialpranker-agentburn (last updated 2026-10-24)