# contextburn (pypi · contextburn)

Run efficiency for coding agents: share of paid tokens that became output, not context re-reading.

- Trust score: 73/100 (medium)
- Change this week: +5
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- pypi · `contextburn`: 73/100 (this document), [markdown](https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn.md), [page](https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn)

## Channel facts

- Registry: `pypi`
- Package: `contextburn`
- Version: `0.2.1`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs setuptools.build_meta at install time, a recognised native-build step with no shell scripting around it.
  - No production dependencies, so there is no dependency health to assess.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 8 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 71/100
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 97 tokens (~48/item across 2 items; 2 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 83/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 50% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 2 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 2 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the contextburn MCP server?

contextburn runs locally as a PyPI package, launched with uvx contextburn. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add ai-arsentev-contextburn -- uvx contextburn
```

### Cursor

```json
{
  "mcpServers": {
    "ai-arsentev-contextburn": {
      "command": "uvx",
      "args": [
        "contextburn"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "ai-arsentev-contextburn": {
      "command": "uvx",
      "args": [
        "contextburn"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add ai-arsentev-contextburn -- uvx contextburn
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-arsentev-contextburn": {
      "type": "local",
      "command": [
        "uvx",
        "contextburn"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-arsentev-contextburn --command uvx --arg contextburn
```

### Hermes

```yaml
mcp_servers:
  ai-arsentev-contextburn:
    command: "uvx"
    args: ["contextburn"]
```

### Netclaw

```json
{
  "McpServers": {
    "ai-arsentev-contextburn": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "contextburn"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add ai-arsentev-contextburn -t stdio -c uvx -a contextburn
```

### Other

```json
{
  "mcpServers": {
    "ai-arsentev-contextburn": {
      "command": "uvx",
      "args": [
        "contextburn"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-20 (score 73, +1)

No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-19 (score 72, +4)

- [functional improvement] Stability: unverified → 0.27

### 2026-09-14 (score 68, 0)

- [functional regression] Security disclosure: unverified → fail

### 2026-09-13 (score 68, 0)

- [functional regression] Security disclosure: fail → unverified

### 2026-09-11 (score 68)

First indexed and scored.

## MCP tools (2)

### `run_efficiency` (~57 tokens)

Run efficiency

Share of paid tokens that became model output versus re-reading of context already sent, over the last N hours of local Claude Code sessions. Reported by tokens and cost-weighted.

Input parameters:

- `hours` (number): Look-back window in hours.

### `spend_breakdown` (~40 tokens)

Spend breakdown

Human-readable breakdown of token spend over the last N hours: run efficiency, sessions, and what specifically inflated the context.

Input parameters:

- `hours` (number)

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn#diagnostics

## Score history

- 2026-09-20: 73
- 2026-09-19: 72
- 2026-09-18: 68
- 2026-09-17: 68
- 2026-09-16: 68
- 2026-09-15: 68
- 2026-09-14: 68
- 2026-09-13: 68
- 2026-09-12: 68
- 2026-09-11: 68

## Common questions

### What is the contextburn MCP server?

contextburn is an MCP server listed in the public MCP registry as ai.arsentev/contextburn. Run efficiency for coding agents: share of paid tokens that became output, not context re-reading. This page covers its PyPI package (contextburn).

### Is the contextburn MCP server safe to use?

contextburn scores 73 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the contextburn MCP server expose?

contextburn exposes 2 tools: run_efficiency, spend_breakdown. Their descriptions and schemas cost roughly 97 tokens of context every time the server is loaded.

### Is the contextburn MCP server still maintained?

contextburn is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the contextburn MCP server under?

contextburn declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- PyPI project: https://pypi.org/project/contextburn/
- Socket report: https://socket.dev/pypi/package/contextburn
- Repository: https://github.com/arsentev-ai/contextburn
- Website: https://arsentev.ai/
- Changelog RSS feed: https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn.json
- HTML version of this page: https://verifymcp.io/servers/ai-arsentev-contextburn/contextburn