原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Agency MCP Server

作者:npupko版本 0.2.2i★ –i在你的电脑上运行
注册名称io.github.npupko/agency-mcp-server

安装

概览

作者提供的说明(英文原文)

On-demand access to 150+ specialist AI agent templates — search, browse, and spawn agents

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: AGENCY_AGENTS_PATH, AGENCY_REPO_URL, AGENCY_AUTO_UPDATE, AGENCY_UPDATE_INTERVAL

你需要

  • npm已安装 Node.js(用于 npx 命令)

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 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "agency": {
      "command": "npx",
      "args": [
        "-y",
        "agency-mcp-server"
      ],
      "env": {
        "AGENCY_AGENTS_PATH": "your-value",
        "AGENCY_REPO_URL": "your-value",
        "AGENCY_AUTO_UPDATE": "your-value",
        "AGENCY_UPDATE_INTERVAL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add agency --env AGENCY_AGENTS_PATH=your-value --env AGENCY_REPO_URL=your-value --env AGENCY_AUTO_UPDATE=your-value --env AGENCY_UPDATE_INTERVAL=your-value -- npx -y agency-mcp-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "agency": {
      "command": "npx",
      "args": [
        "-y",
        "agency-mcp-server"
      ],
      "env": {
        "AGENCY_AGENTS_PATH": "your-value",
        "AGENCY_REPO_URL": "your-value",
        "AGENCY_AUTO_UPDATE": "your-value",
        "AGENCY_UPDATE_INTERVAL": "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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "agency": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agency-mcp-server"
      ],
      "env": {
        "AGENCY_AGENTS_PATH": "your-value",
        "AGENCY_REPO_URL": "your-value",
        "AGENCY_AUTO_UPDATE": "your-value",
        "AGENCY_UPDATE_INTERVAL": "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。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • AGENCY_AGENTS_PATH env
    Custom path to agent templates directory
  • AGENCY_REPO_URL env
    Git repo URL to clone agent templates from
  • AGENCY_AUTO_UPDATE env
    Enable automatic template updates (true/false)
  • AGENCY_UPDATE_INTERVAL env
    Hours between update checks

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。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 npupko 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5692 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5692 个服务器的 8% 更新
  • 基础检查结果等于或优于此分类中其他 5692 个服务器的 100%

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。

常见问题

Agency MCP Server 安全吗?

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。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.2)于7个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

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

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万前天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万22天前更新

在你的电脑上运行

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者:exa-labs正在增长★ 52132个月前更新

在云端运行✓ exa.ai

作者的 README

打开 README

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。

agency-mcp-server

One MCP config entry. 150+ specialist agents on demand. No manual setup.

Your AI assistant is a generalist. Sometimes you need a specialist -- a game economy designer, a security auditor, a technical writer. This MCP server gives your assistant instant access to 150+ expert agent templates. Describe what you need, it finds the right agent and spawns it.

You: "Help me design a balanced game economy"

Claude: [searches -> finds Game Economy Designer -> spawns it -> expert response]

Templates auto-fetch on first run from agency-agents and stay updated. You don't touch a thing.

Why not just install agents locally?

You can. The agency-agents install script copies all 160+ agent files directly into your tool's config directory (e.g. ~/.claude/agents/). It works -- but every agent's name and description is loaded into the context window of every conversation, whether you use them or not.

We measured it:

ApproachContext costWhen
Installed agents (~/.claude/agents/)~8,300 tokensEvery conversation, always
MCP server (idle)~55 tokensEvery conversation
MCP server (searching)~350 tokensOnly when you search
MCP server (using an agent)~2,700 tokensOnly when you spawn one (median)

That's a 150x reduction in baseline context usage. You get the same 160+ agents, but you only pay for the one you're actually using.

How we measured this

Installed agents (8,300 tokens): We ran the agency-agents install script (install.sh --tool claude-code), which copied 162 agent files to ~/.claude/agents/. Then opened a fresh Claude Code session and ran /context. Claude Code reported "Custom agents: 8.3k tokens" -- loaded into every conversation regardless of whether any agent is used.

MCP idle (55 tokens): With the MCP server configured instead, /context shows only the two deferred tool names (agency_search, agency_browse) and a brief server description in the system prompt. No agent data is loaded.

MCP searching (350 tokens): Measured by tokenizing the full JSON tool schemas that get loaded when the assistant calls ToolSearch to resolve the agency_search and agency_browse tools. Counted with @anthropic-ai/tokenizer.

MCP using an agent (2,700 tokens): The median token count across all 145 agent files, measured with @anthropic-ai/tokenizer. Only the single agent file you're actually using gets loaded into context. The range is 383–12,724 tokens depending on the agent (p25: 1,549, p75: 3,584).

Quick Start

Claude Code

As a plugin:

/plugin marketplace add npupko/agency-mcp-server

/plugin install agency@agency-mcp-server

Or via CLI:

claude mcp add agency -- npx -y agency-mcp-server
Cursor, Windsurf, and other MCP clients

Add to your MCP config:

{

"mcpServers": { "agency": { "command": "npx", "args": ["-y", "agency-mcp-server"] } } }

That's it. First launch clones templates to ~/.cache/agency-mcp-server/ and pulls updates every 24 hours.

Verify it works

Ask your assistant:

"Search for a game economy designer agent"

You should see results from the agency_search tool. If it's the first run, templates will auto-download (~30 seconds).

How It Works

Your assistant gets four tools:

  1. `agency_search(query, division?)` -- describe a task, get matching agents with spawn instructions
  2. `agency_browse(division?)` -- explore divisions and agents when you want to see what's available
  3. `agency_status()` -- check index freshness: agent count, last update time, whether an update is available
  4. `agency_update()` -- pull latest templates from git and rebuild the search index without restarting

When you ask for help with something specific, your assistant calls agency_search, picks the best match, and spawns a subagent with that specialist's full system prompt. You get an expert response without ever touching a config file.

What's available

Agents are organized into divisions:

DivisionExamples
EngineeringSoftware Architect, DevOps Engineer, Technical Writer
DesignUI Designer, UX Researcher, Design Systems
Game DevelopmentGame Economy Designer, Game Mechanics Designer
MarketingContent Strategist, SEO Specialist, Email Marketing
Security & SpecializedSecurity Auditor, Data Scientist, Legal Analyst
...and moreAcademic, Sales, Strategy, Support, Testing, Spatial Computing

Configuration

All configuration is through environment variables in your MCP config:

VariableDefaultDescription
AGENCY_AGENTS_PATH~/.cache/agency-mcp-server/agency-agentsPath to agent templates. Set this to use your own templates instead of auto-cloning
AGENCY_REPO_URLhttps://github.com/msitarzewski/agency-agents.gitGit repo to clone templates from. Point at your fork
AGENCY_AUTO_UPDATEtrueSet to false to disable automatic pulls
AGENCY_UPDATE_INTERVAL24Hours between update checks
Use your own templates

Point at a local directory:

{

"mcpServers": { "agency": { "command": "npx", "args": ["-y", "agency-mcp-server"], "env": { "AGENCY_AGENTS_PATH": "/path/to/your/agent-templates" } } } }

Or clone from your own repo:

{

"mcpServers": { "agency": { "command": "npx", "args": ["-y", "agency-mcp-server"], "env": { "AGENCY_REPO_URL": "https://github.com/yourorg/custom-agents.git" } } } }

Template format

Each agent is a Markdown file with YAML front-matter, organized by division:

engineering/

software-architect.md devops-engineer.md design/ ui-designer.md game-development/ game-economy-designer.md

---

name: Software Architect description: Expert software architect specializing in system design...


Full agent system prompt goes here.

The server indexes the name and description fields for search. The full Markdown body becomes the agent's system prompt when spawned.

MCP Interface

Tools
  • `agency_search(query, division?)` -- find agents by task description, returns matches with file paths and a ready-to-use spawn template
  • `agency_browse(division?)` -- list all divisions, or list agents within a specific division
  • `agency_status()` -- check index freshness: agent count, last update time, whether an update is due
  • `agency_update()` -- pull latest templates from git and rebuild the search index at runtime
Resources
  • `agency://agents` -- full agent index as JSON
  • `agency://divisions` -- division list with counts and examples
Prompts
  • `use-agent` -- describe a task, get the best-matching agent with spawn instructions

Development

npm install

npm run build

Run with auto-fetched templates

node dist/index.js

Run with local templates

AGENCY_AGENTS_PATH=./my-agents node dist/index.js

Type checking

npm run typecheck

MCP Inspector

npm run inspect

Credits

Agent templates from agency-agents by @msitarzewski.

License

MIT

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