Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http tools-for-agents https://api.toolsforagents.tools/mcp --header 'Authorization: your-value'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"tools-for-agents": {
"url": "https://api.toolsforagents.tools/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"tools-for-agents": {
"type": "http",
"url": "https://api.toolsforagents.tools/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 max124vip-dev 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.1.0)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Tethered Trust
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Tools for Agents
Decision layer for AI agents — plan workflows, execute 100+ tools, and delegate multi-step missions.
Not a flat API catalog. An orchestration platform built for autonomous agents.
What · Who · How · Quick start · Examples · Integrations · Docs
Tools for Agents is a hosted API platform that gives AI agents real-world capabilities: read websites, search the web, extract PDFs, run OCR, build RAG pipelines, verify facts, and execute pre-built tool chains — all through machine-readable REST, MCP, and A2A interfaces.
Instead of guessing which of 100 endpoints to call, agents start with the Agent Advisor: describe a goal, get a workflow plan, cost estimate, and confidence score — then invoke tools with copy-paste examples that prevent validation errors.
| You get | Instead of |
|---|---|
POST /v1/advisor → plan + alternatives | Manually picking from 100 endpoints |
GET /v1/tools/{tool}/examples → exact JSON bodies | Trial-and-error 422 errors |
POST /v1/chains/run → multi-step pipelines | Wiring 5 tools yourself |
POST /a2a/v1/skills/.../invoke → delegate to remote agent | Low-level REST for every step |
pip install agenttools-client → self-healing SDK | Raw httpx + custom retry logic |
Live service: toolsforagents.tools · API: api.toolsforagents.tools
| Audience | Use case |
|---|---|
| Autonomous AI agents | Self-register, plan with Advisor, invoke tools — no human in the loop |
| Agent builders (LangChain, CrewAI, custom orchestrators) | REST + Python SDK + tool chains |
| IDE agents (Cursor, Claude Desktop, Windsurf) | Remote MCP at /mcp — configs |
| Multi-agent systems | A2A Agent Card + 13 skills — delegate research, ingest, missions |
| Developers prototyping agents | Free tier: 5,000 req/day, instant API key, Swagger UI |
Critical rule for agents: never ask a human for an API key.
Register programmatically:
POST /v1/registerwith body{}.
┌──────────────┐ 1. Plan ┌─────────────────────┐
│ Your agent │ ──────────────────► │ Agent Advisor │ │ (any stack) │ POST /advisor │ workflow · cost │ └──────┬───────┘ └──────────┬──────────┘ │ │ │ 2. Register (once) │ 3. Execute │ POST /register {} ▼ │ ┌─────────────────────┐ └────────────────────────────►│ Tools for Agents │ REST · MCP · A2A · SDK │ extract · pdf · rag │ │ chains · missions │ └──────────┬──────────┘ │ ┌─────────────────────────────┼─────────────────────────────┐ ▼ ▼ ▼ Web & documents Trust & cognitive Orchestration extract, ingest, pdf verify, confidence, bias chains, workflows
Typical agent loop:
GET /v1/onboarding — read the playbookPOST /v1/advisor — plan before acting (0 units)POST /v1/dry-run — probe URL cost/JS (~450 ms, 0 units)POST /v1/register {} — get API key (no email)GET /v1/tools/{tool}/examples — copy exact request bodyPOST /v1/chains/run · or A2A skillpip install agenttools-client
import asyncio
from agenttools_client import AsyncAgentToolsClient
async def main(): async with AsyncAgentToolsClient() as client:
plan = await client.advisor("Extract markdown from a blog post URL") page = await client.extract("https://example.com", format="markdown") chain = await client.a2a.run_chain("article_read", {"url": "https://example.com"})
asyncio.run(main())
PyPI: pypi.org/project/agenttools-client · Demo: examples/sdk_demo.py
# Plan (no auth)
curl -X POST https://api.toolsforagents.tools/v1/advisor \ -H "Content-Type: application/json" \ -d '{"goal":"Extract markdown from example.com"}'
curl -X POST https://api.toolsforagents.tools/v1/register \ -H "Content-Type: application/json" -d '{}'
curl -X POST https://api.toolsforagents.tools/v1/extract \ -H "Authorization: Bearer sk_live_..." \ -H "Content-Type: application/json" \ -d '{"url":"https://example.com","format":"markdown"}'
{
"mcpServers": { "tools-for-agents": { "type": "streamable-http", "url": "https://api.toolsforagents.tools/mcp", "headers": { "Authorization": "Bearer sk_live_YOUR_KEY" } } } }
Copy-paste configs: mcp-configs/ · Guide: docs/MCP_QUICKSTART.md
git clone https://github.com/max124vip-dev/tools-for-agents.git
cd tools-for-agents pip install -e ./agenttools_client python examples/sdk_demo.py python examples/advisor_flow.py "Research AI agent API best practices"
curl -X POST https://api.toolsforagents.tools/v1/agent/research \
-H "Authorization: Bearer sk_live_..." \ -H "Content-Type: application/json" \ -d '{"query":"solid-state battery news 2025","max_results":5}'
curl -X POST https://api.toolsforagents.tools/v1/chains/run \
-H "Authorization: Bearer sk_live_..." \ -H "Content-Type: application/json" \ -d '{"chain_id":"pdf_summary","inputs":{"url":"https://example.com/report.pdf"}}'
curl -X POST https://api.toolsforagents.tools/a2a/v1/skills/youtube-summary/invoke \
-H "Authorization: Bearer sk_live_..." \ -H "Content-Type: application/json" \ -d '{"input":{"url":"https://www.youtube.com/watch?v=..."}}'
# Wrong body → SDK fetches /v1/tools/{tool}/examples and retries once
await client.json("POST", "/v1/confidence/estimate", json={})
More: examples/ · 400+ API examples: GET /v1/tools/examples/index
| Layer | Description |
|---|---|
| Agent Advisor | Goal → workflow, confidence, cost, alternatives (0 units) |
| 100+ REST tools | Web, PDF, OCR, search, RAG, trust, crypto, validation… |
| 28 tool chains | pdf_summary, youtube_summary, article_read, research_with_confidence… |
| 13 A2A skills | Delegate ingest, research, missions, chains to remote agent |
| 98 MCP tools | Cursor, Claude Desktop, Smithery — catalog |
| Python SDK | Auto auth · 422 heal · 5xx retry · PyPI |
| Commons memory | Shared agent learnings — POST /v1/commons/recall (public read) |
| CRP Discovery | Quality Capability Discovery — POST /v1/crp/resolve (free) → execute → feedback |
| x402 payments | Pay per call with USDC — no account (docs) |
Free tier: 5,000 requests/day · 120/min · 500 GPU units/month · instant register
Live latency (p50): dry-run ~450 ms · register ~700 ms · advisor ~600 ms
| Protocol | Entry point | Best for |
|---|---|---|
| REST + OpenAPI | api.toolsforagents.tools/docs | Any HTTP client |
| Python SDK | pip install agenttools-client | Python agents & scripts |
| MCP | api.toolsforagents.tools/mcp | IDE agents |
| A2A | /.well-known/agent-card.json | Multi-agent orchestrators |
| llms.txt | toolsforagents.tools/llms.txt | LLM crawlers |
| Doc | Description |
|---|---|
| Complete API Guide | Mandatory reading for agents — prevents 422, covers chains & SDK |
| CRP Spec v0 | Quality Capability Discovery — resolve, feedback, provenance |
| CRP Roadmap | Implementation phases 0–7 |
| Capability Taxonomy | 31 stable capability IDs |
| Agent Passport Spec | External agent identity |
| MCP Quick Start | Cursor, Claude, Windsurf configs |
| A2A Remote Agent | 13 skills + invoke examples |
| Quickstart | Human-friendly overview |
| x402 wallet payments | Pay-per-call without signup |
| Architecture | High-level system design |
| Registries (Smithery) | MCP catalog publishing |
Machine-readable discovery:
| Resource | URL |
|---|---|
| Agent playbook | GET https://api.toolsforagents.tools/v1/onboarding |
| Tool index | GET https://api.toolsforagents.tools/.well-known/tool-index.json |
| Examples index | GET https://api.toolsforagents.tools/v1/tools/examples/index |
| Agent Card (A2A) | GET https://api.toolsforagents.tools/.well-known/agent-card.json |
| CRP resolve | POST https://api.toolsforagents.tools/v1/crp/resolve |
| CRP capabilities | GET https://api.toolsforagents.tools/v1/crp/capabilities |
This is a public integration repository — docs, SDK, examples, and agent manifests.
| Included | Hosted on our servers (not in repo) |
|---|---|
| agenttools_client/ — Python SDK | Full API server source |
| examples/ — runnable scripts | Admin & billing internals |
| agent/ — llms.txt & agent.txt | Production infrastructure |
| docs/ · mcp-configs/ | Proprietary tool implementations |
You integrate with the live API — this repo is not a self-hostable clone.
只显示了开头部分;其余内容请在仓库中阅读