API搜索
- 作者仓库星标 39
- 作者更新于 实时读取
- 作者仓库 awesome-omni-skill
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @diegosouzapw · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 需要 · OpenAI / GitHub / Notion / Stripe
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- Python
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 允许外网请求
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: notmcp
description: Local tool system for API integrations and automation. Use when connecting to external services…
category: AI 智能
runtime: Python
---
# notmcp 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Discovering Tools / Running Tools / Handling Credentials”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Discovering Tools / Running Tools / Handling Credentials”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、会按任务需要访问外部网络、需要准备 OpenAI / GitHub / Notion / Stripe API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;会按任务需要访问外部网络;需要准备 OpenAI / GitHub / Notion / Stripe API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文出现了 `/me`、`/user`、`/auth` 这类斜杠命令;如果你的 Agent 支持命令触发,优先用命令开场,再补充目标和边界。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“Discovering Tools / Running Tools / Handling Credentials”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: notmcp
description: Local tool system for API integrations and automation. Use when connecting to external services…
category: AI 智能
source: diegosouzapw/awesome-omni-skill
---
# notmcp
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Discovering Tools / Running Tools / Handling Credentials」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;会按任务需要访问外部网络;需要准备 OpenAI / GitHub / Notion / Stripe API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "notmcp" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Discovering Tools / Running Tools / Handling Credentials
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Python | 读取文件、写入/修改文件、执行终端命令 | 会按任务需要访问外部网络
安全层 -> 需要准备 OpenAI / GitHub / Notion / Stripe API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} notmcp
You have access to a local toolbox of executable scripts. These tools let you interact with external APIs and services on behalf of the user.
Discovering Tools
To see what tools are available:
~/.claude/skills/notmcp/bin/notmcp list
To search for tools by keyword:
~/.claude/skills/notmcp/bin/notmcp search <query>
Running Tools
Run tools with JSON input:
~/.claude/skills/notmcp/bin/notmcp run <tool-name> --input '{"key": "value"}'
Tools return JSON to stdout. Exit code 0 means success.
If a tool doesn't need input, you can omit the --input flag:
~/.claude/skills/notmcp/bin/notmcp run <tool-name>
Handling Credentials
If a tool needs credentials (API keys, tokens), it will fail with an error like:
Error: Missing credential(s): POSTHOG_API_KEY
When this happens:
- Ask the user for the credential value
- Store it securely:
echo "the-secret-value" | ~/.claude/skills/notmcp/bin/notmcp creds set CREDENTIAL_NAME
To see what credentials are already stored:
~/.claude/skills/notmcp/bin/notmcp creds list
Connecting to Services
When the user wants to connect to a service, guide them interactively, one step at a time. Wait for the user to complete each step before proceeding to the next.
Connection Process (Interactive)
Step 1: Open the credentials page
- Run
open "URL"to open the page in their browser - Tell them what page opened and wait for confirmation they see it
Step 2: Guide them through the UI (one action at a time)
- Give ONE instruction, then wait for them to do it
- Don't dump all steps at once - be conversational
- Example: "Click 'Generate new token'" → wait → "Now copy the token that appears"
Step 3: Collect the credential
- Ask them to paste the token/key
- Store it immediately when they provide it
Step 4: Verify silently
- Run a verification API call
- Only tell them if it fails - if it works, just confirm "Connected!"
Important: Be Interactive
BAD (dumping everything):
Here's how to connect:
1. Go to URL
2. Click X
3. Click Y
4. Copy Z
5. Paste it here
GOOD (interactive):
I'll open the GitHub tokens page for you.
[opens browser]
Let me know when you see the page.
[user: "ok I see it"]
Click "Generate new token" at the top.
[user: "done"]
Now copy the token that appears and paste it here.
Verifying Connections
After storing credentials, verify they work by making a simple API call:
- Most REST APIs have a /me, /user, or /auth endpoint
- Use the http-get tool or make a quick urllib request
- If it fails, troubleshoot with the user before proceeding
- If it works, just say "Connected!" - don't over-explain
Common Services
Google (Gmail, Drive, Calendar) - App Password
- URL: https://myaccount.google.com/apppasswords
- Requires 2FA enabled on the account
- Guide: "Select 'Other (Custom name)', enter 'notmcp', click Generate"
- Store as: GOOGLE_APP_PASSWORD and GOOGLE_EMAIL
GitHub - Personal Access Token
- URL: https://github.com/settings/tokens/new?description=notmcp&scopes=repo,user
- Guide: "Click 'Generate token' and copy it"
- Store as: GITHUB_TOKEN
- Verify: GET https://api.github.com/user with Authorization header
Slack - Bot Token
- URL: https://api.slack.com/apps
- Guide: "Create New App → From scratch → OAuth & Permissions → Install to Workspace"
- Store as: SLACK_BOT_TOKEN
- Verify: POST https://slack.com/api/auth.test
Notion - Integration Token
- URL: https://www.notion.so/my-integrations
- Guide: "New integration → Name 'notmcp' → Copy the Internal Integration Secret"
- Store as: NOTION_TOKEN
- Remind user to share specific pages with the integration
OpenAI - API Key
- URL: https://platform.openai.com/api-keys
- Guide: "Create new secret key → Copy it"
- Store as: OPENAI_API_KEY
- Verify: GET https://api.openai.com/v1/models
Linear - API Key
- URL: https://linear.app/settings/api
- Store as: LINEAR_API_KEY
Stripe - Secret Key
- URL: https://dashboard.stripe.com/apikeys
- Store as: STRIPE_SECRET_KEY
Other Services
For services not listed:
- Search for their API or Developer documentation
- Find where to create API keys or tokens
- Guide the user through the process
- Store with a descriptive name: {SERVICE}_API_KEY
- Verify with a simple API call before building tools
Using Context7 for API Documentation (Optional)
Context7 provides up-to-date API documentation. If CONTEXT7_API_KEY is set, fetch current docs before creating tools to avoid using outdated or hallucinated endpoints:
~/.claude/skills/notmcp/bin/notmcp run context7-docs --input '{"library": "googleapis/gmail", "topic": "send"}'
To set up Context7:
- Open: https://context7.com/dashboard
- Sign up (free) and copy your API key
- Store:
echo "xxx" | ~/.claude/skills/notmcp/bin/notmcp creds set CONTEXT7_API_KEY
Without Context7, you can still create tools using your knowledge, but results may be less accurate for newer APIs.
Creating Tools
Only create new tools when the user explicitly asks (e.g., "save this as a tool", "make this reusable", "create a tool for this").
To create a new tool:
~/.claude/skills/notmcp/bin/notmcp create tool-name
This creates a template at ~/.claude/skills/notmcp/scripts/tool-name.py.
Then edit the script to implement the tool logic. Follow these conventions:
Tool Contract
- Input: JSON via stdin (parsed with
json.load(sys.stdin)) - Output: JSON to stdout (use
print(json.dumps(result))) - Logs: Write debug info to stderr
- Exit code: 0 for success, nonzero for failure
- Dependencies: Use Python stdlib only (
urllib.request,json,os, etc.)
Tool Header Format
Every tool must have a docstring header declaring its metadata:
#!/usr/bin/env python3
"""
name: tool-name
description: What this tool does (one line)
credentials:
- API_KEY_NAME
- ANOTHER_SECRET
input:
param1: string (required)
param2: int (optional, default 10)
output:
result: description of output
"""
Example Tool Structure
#!/usr/bin/env python3
"""
name: example-api
description: Fetch data from Example API
credentials:
- EXAMPLE_API_KEY
input:
query: string (required)
output:
results: list of matching items
"""
import json
import os
import sys
from urllib.request import urlopen, Request
def main():
# Read input
inp = json.load(sys.stdin) if not sys.stdin.isatty() else {}
# Get credentials (injected by notmcp run)
api_key = os.environ["EXAMPLE_API_KEY"]
# Make API call
query = inp.get("query", "")
req = Request(f"https://api.example.com/search?q={query}")
req.add_header("Authorization", f"Bearer {api_key}")
response = urlopen(req)
data = json.loads(response.read())
# Return result
print(json.dumps({"results": data["items"]}))
if __name__ == "__main__":
main()
Best Practices
- Handle pagination - Don't return unbounded results. Implement limits and cursors.
- Handle rate limits - Add delays or retry logic for APIs with rate limits.
- Return compact output - Summarize large responses. Agents work better with concise data.
- Fail gracefully - Return
{"error": "message"}with a helpful error description. - Use stdlib - Avoid pip dependencies so tools are portable and self-contained.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核