Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Talljack/mcp_server_trendingWrote 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/rules/talljack/mcp_server_trending/development)<a href="https://agentmods.dev/rules/talljack/mcp_server_trending/development"><img src="https://agentmods.dev/badge/rules/talljack/mcp_server_trending/development/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/rules/talljack/mcp_server_trending/development"><img src="https://agentmods.dev/badge/rules/talljack/mcp_server_trending/development.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 | $0.00000 | $0.02432 |
| Opus 5.5 | $0.00000 | $0.00973 |
| Sonnet 5.5 | $0.00000 | $0.00486 |
| Haiku 4.5 | $0.00000 | $0.00243 |
Grade A, and why
development 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 — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Trending 开发规范
1. 开发前准备(必须执行)
在开始任何新功能开发之前,必须执行以下步骤:
1.1 切换到 main 分支并更新
# 切换到 main 分支
git checkout main
# 拉取最新的 main 分支代码
git pull origin main
1.2 基于用户意图创建新分支
根据用户的开发需求,创建语义化的分支名称:
# 分支命名规范
# - feat/xxx: 新功能
# - fix/xxx: Bug 修复
# - docs/xxx: 文档更新
# - refactor/xxx: 代码重构
# - test/xxx: 测试相关
git checkout -b feat/add-xxx-fetcher # 示例:添加新的 fetcher
git checkout -b fix/xxx-serialization # 示例:修复序列化问题
git checkout -b docs/update-readme # 示例:更新文档
2. 新 Fetcher 开发规范
2.1 目录结构
新的 fetcher 必须遵循以下目录结构:
src/mcp_server_trending/
├── fetchers/
│ └── {platform_name}/ # 新平台目录
│ ├── __init__.py # 导出 Fetcher 类
│ └── fetcher.py # Fetcher 实现
└── models/
└── {platform_name}.py # 数据模型定义
2.2 Model 定义规范
所有数据模型必须继承自 BaseModel:
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any
from .base import BaseModel
@dataclass
class YourModel(BaseModel):
"""数据模型描述"""
rank: int
id: str
name: str
url: str
# ... 其他字段
# 可选字段使用默认值
description: str | None = None
created_at: datetime | None = None
tags: list[str] = field(default_factory=list)
2.3 Fetcher 实现规范
from typing import Any
from ..base import BaseFetcher
from ...models.base import TrendingResponse
from ...models.{platform} import YourModel
class YourFetcher(BaseFetcher):
"""Fetcher 描述"""
PLATFORM = "{platform_name}"
BASE_URL = "https://api.example.com"
async def fetch_xxx(
self,
limit: int = 20,
use_cache: bool = True,
) -> TrendingResponse:
"""获取数据的方法描述"""
cache_key = f"{self.PLATFORM}:xxx:limit={limit}"
# 检查缓存
if use_cache:
cached = self._get_from_cache(cache_key)
if cached:
return cached
try:
# 实现数据获取逻辑
items = []
# ... 获取和解析数据
response = TrendingResponse(
success=True,
platform=self.PLATFORM,
data=items,
metadata={"limit": limit},
)
# 保存到缓存
self._save_to_cache(cache_key, response)
return response
except Exception as e:
return TrendingResponse(
success=False,
platform=self.PLATFORM,
error=str(e),
)
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 First seen · 377 lines · 0 tokens per session scan A 1ebc8d23ae80
development is a cursor rule published in the GitHub repository Talljack/mcp_server_trending (2 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,432 tokens. 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.
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