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.
npx agentmods add instructions/ljzloser/mcp_tools/pluginsgit clone --depth 1 https://github.com/ljzloser/mcp_toolsWhat 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 | $0.01539 | $0.01539 |
| Opus 5 | $0.00770 | $0.00770 |
| Sonnet 5 | $0.00308 | $0.00308 |
| Haiku 4.5 | $0.00154 | $0.00154 |
Grade A, and why
plugin-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 2d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Tool Hub 插件开发指南
插件结构
每个插件目录包含:
__init__.py— 导出PLUGIN_CLASS和WIDGET_CLASS(可选)backend.py— 插件后端逻辑widget.py— 可选的 PySide6 UI 组件README.md— 插件文档(必须)
目录名不能以 _ 或 . 开头。
后端模式
基本结构
from api.base_plugin import BasePlugin
from api.tool import ToolDef, MCPToolResult
from api.config import ConfigModel, StringField
from pydantic import BaseModel, Field
# 可选:配置模型
class MyPluginConfig(ConfigModel):
api_key = StringField(default="", label="API 密钥", description="...")
# 工具参数模型
class MyToolArgs(BaseModel):
input_text: str = Field(description="输入文本")
# 插件类
class MyPlugin(BasePlugin[MyPluginConfig]):
config_class = MyPluginConfig
# 工具声明 — 使用类属性 ToolDef
my_tool = ToolDef(
name="my_tool",
args_model=MyToolArgs,
description="工具描述"
)
@property
def meta(self) -> PluginMeta:
return PluginMeta(
name="my_plugin",
display_name="我的插件",
version="1.0.0",
description="插件功能描述",
author="MCP Tool Hub",
icon="🔧"
)
async def handle_my_tool(self, args: MyToolArgs) -> MCPToolResult:
try:
result = f"处理: {args.input_text}"
return MCPToolResult(content=[{"type": "text", "text": result}])
except Exception as e:
return MCPToolResult(
content=[{"type": "text", "text": f"错误: {e}"}],
is_error=True
)
工具声明规范
- 使用
ToolDef类属性(非装饰器) name: 工具唯一名称,全局唯一args_model: Pydantic BaseModel,用于参数验证和 JSON Schema 生成description: 工具功能描述,供 AI 客户端使用
返回格式
统一使用 MCPToolResult:
# 成功
MCPToolResult(content=[{"type": "text", "text": "结果"}])
# 错误
MCPToolResult(content=[{"type": "text", "text": "错误信息"}], is_error=True)
访问配置
class MyPlugin(BasePlugin[MyPluginConfig]):
async def handle_my_tool(self, args):
# 直接通过 self.config 访问配置字段
api_key = self.config.api_key
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.
- 2d ago First seen · 228 lines · 1,539 tokens per session scan A 4ea0bbe8d682
plugin-development is an instructions file published in the GitHub repository ljzloser/mcp_tools (4 stars, last pushed 2mo ago), licensed MIT. It adds 1,539 tokens to every session, about $0.0077 per session on Opus 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.