
Agency Mcp Server
io.github.npupko由 GitHub 账号 npupko 发布v0.2.2更新于 Oct 24, 2026
On-demand access to 150+ specialist AI agent templates — search, browse, and spawn agents
概览
一个本地 MCP 服务器,为助手提供 150 多个专家代理模板的可搜索库,并能针对任务启动最匹配的代理。
- 可以做什么
- 按任务描述搜索专家代理模板,可限定某个分部,返回匹配项及启动说明和文件路径。浏览分部,或列出某个分部下的代理。检查索引新鲜度:代理数量、上次更新时间、是否有可用更新。从 git 拉取最新模板并在不重启的情况下重建搜索索引。以资源形式读取完整代理索引和分部列表,或使用提示词按任务描述取得最匹配的代理。
- 适用场景
- 适合希望助手扮演专家角色(例如游戏经济设计师、安全审计员或技术文档撰写者),又不想把所有代理文件都装入上下文窗口的场景。也适合偏好按需查找代理、而非长期加载整个代理目录的用户。
- 运行要求
- 通过 stdio 在本地运行,通常经 npx 启动,需要 Node.js 和网络访问。首次启动会从 git 仓库克隆模板到本地缓存,并定期刷新。可选环境变量:AGENCY_AGENTS_PATH、AGENCY_REPO_URL、AGENCY_AUTO_UPDATE、AGENCY_UPDATE_INTERVAL。未声明身份验证。
安装
在 SourceWeft 中
- 打开 控制台中的 Agency Mcp Server,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
agency-mcp-server
[npm version] [JSR] [CI] [License: MIT]
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.
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:
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:
Or via CLI:
Cursor, Windsurf, and other MCP clients
Add to your MCP config:
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:
agency_search(query, division?)-- describe a task, get matching agents with spawn instructionsagency_browse(division?)-- explore divisions and agents when you want to see what's availableagency_status()-- check index freshness: agent count, last update time, whether an update is availableagency_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:
Configuration
All configuration is through environment variables in your MCP config:
Use your own templates
Point at a local directory:
Or clone from your own repo:
Template format
Each agent is a Markdown file with YAML front-matter, organized by division:
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 templateagency_browse(division?)-- list all divisions, or list agents within a specific divisionagency_status()-- check index freshness: agent count, last update time, whether an update is dueagency_update()-- pull latest templates from git and rebuild the search index at runtime
Resources
agency://agents-- full agent index as JSONagency://divisions-- division list with counts and examples
Prompts
use-agent-- describe a task, get the best-matching agent with spawn instructions
Development
Credits
Agent templates from agency-agents by @msitarzewski.
License
MIT
来源:README.md,提交 e82d938
工具
0版本历史
1- v0.2.2最新Sep 16, 2026
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