Borrowing it
Nothing to install: this file belongs to YC-CLT/VLM-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/YC-CLT/VLM-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/YC-CLT/VLM-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/yc-clt/vlm-mcp/agents-md)<a href="https://agentmods.dev/instructions/yc-clt/vlm-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/yc-clt/vlm-mcp/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/yc-clt/vlm-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/yc-clt/vlm-mcp/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02002 | $0.02002 |
| Opus 5.5 | $0.00801 | $0.00801 |
| Sonnet 5.5 | $0.00400 | $0.00400 |
| Haiku 4.5 | $0.00200 | $0.00200 |
Grade A, and why
VLM-mcp AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
环境
- Python 3.11,uv 管理依赖
- config.py 集中配置所有常量,pyproject.toml 管理依赖
- 命令:用
cmd-exec-mcp
关键文件
| 文件 | 作用 |
|---|---|
main.py |
入口,纯启动脚本,启动 MCP |
server.py |
MCP Server,7 个工具,stdio 传输 |
config.py |
所有常量 + config.json 加载 |
config.json |
敏感配置(API Key、模型路径),不入 git |
llama_launcher.py |
llama-server 子进程生命周期(启/停/健康检查) |
providers/ocr_provider.py |
OCR Provider(RapidOCR 懒加载 + 延迟卸载) |
providers/openai_compat.py |
OpenAI 兼容 API 客户端(AsyncOpenAI)+ llama 懒启动 |
session_manager.py |
会话 CRUD + 超时清理 + 满时驱逐 |
cache.py |
L1 图片缓存(LRU)+ L2 响应缓存(LRU + TTL) |
image_utils.py |
图片源解析(路径/URL/Data URI/Base64 回退) |
logger.py |
单例 logger → log.txt |
关键常量
| 常量 | 位置 | 说明 |
|---|---|---|
IMAGE_MAX_SIZE_MB |
config.py |
图片最大体积 (20MB) |
IMAGE_DOWNLOAD_TIMEOUT |
config.py |
图片下载超时秒数 (10s) |
CACHE_IMAGE_MAX_ENTRIES |
config.py |
L1 缓存上限 (100) |
CACHE_RESPONSE_MAX_ENTRIES |
config.py |
L2 缓存上限 (500) |
CACHE_RESPONSE_TTL_ONLINE |
config.py |
在线后端缓存 TTL (3600s) |
CACHE_RESPONSE_TTL_LOCAL |
config.py |
本地后端缓存 TTL (1800s) |
SESSION_TTL |
config.py |
会话超时秒数 (1800s) |
SESSION_MAX |
config.py |
每后端最大会话数 (5) |
LOG_LEVEL |
config.py |
日志级别 ("INFO") |
LLAMA_DEFAULTS |
config.py |
llama-server 启动参数默认值 |
BACKENDS |
config.py |
从 config.json 加载的后端配置 |
CACHE_ENABLED |
config.py |
从 config.json 加载的缓存开关 |
规则
- monkeypatch 必须用
import config+config.X:from config import X创建本地副本,monkeypatch 无法穿透;executor 同理 patchexecutors.模块名.X - config 重命名全量 grep:常量改名/移除后搜索所有引用
- 跨 Task 依赖等待:并行派发时先检查上游产物是否存在
工具
- 部分工具有相应的skill
- MCP详见
mcp_tools_summary.csv Read无法访问D:\Temp,MCP 长输出需Copy-Item到项目根目录,正则替换\\n为\n- Edit
replace_all错误:replace_all=True无法使用。优先用 PowerShellSelect-String+ 正则做精确替换,或手动逐处 Edit - 浏览器操控用
chrome-devtools-edge(Edge CDP),禁止用cua-driver操控浏览器 - WebFetch 无法使用:用
wet-mcp extract
工作流
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +3 lines · +176 tokens per session a75ed2776258
- 2mo ago Changed · +5 lines · +226 tokens per session 21058e7157da
- 2mo ago First seen · 82 lines · 1,600 tokens per session scan A 4a427c014cff
VLM-mcp AGENTS.md is an instructions file published in the GitHub repository YC-CLT/VLM-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 2,002 tokens to every session, about $0.0080 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
VLM-mcp AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| VLM-mcp AGENTS.mdYC-CLT/VLM-mcp | Instructions file | 0 | 1mo ago | MIT | A | 2,002 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |