
Agency Mcp Server
io.github.npupko由 GitHub 帳號 npupko 發布v0.2.2更新於 Oct 24, 2026
On-demand access to 150+ specialist AI agent templates — search, browse, and spawn agents
概覽
一個本機 MCP 伺服器,為助理提供 150 多個專家代理範本的可搜尋資料庫,並能針對任務啟動最相符的代理。
- 可以做什麼
- 依任務描述搜尋專家代理範本,可限定某個分部,回傳符合項目及啟動說明與檔案路徑。瀏覽分部,或列出某個分部下的代理。檢查索引新鮮度:代理數量、上次更新時間、是否有可用更新。從 git 拉取最新範本並在不重新啟動的情況下重建搜尋索引。以資源形式讀取完整代理索引與分部清單,或使用提示詞依任務描述取得最相符的代理。
- 適用情境
- 適合希望助理扮演專家角色(例如遊戲經濟設計師、安全稽核員或技術文件撰寫者),又不想把所有代理檔案都載入上下文視窗的情境。也適合偏好按需查找代理、而非長期載入整個代理目錄的使用者。
- 執行需求
- 透過 stdio 在本機執行,通常經由 npx 啟動,需要 Node.js 與網路存取。首次啟動會從 git 儲存庫複製範本到本機快取,並定期更新。選用環境變數:AGENCY_AGENTS_PATH、AGENCY_REPO_URL、AGENCY_AUTO_UPDATE、AGENCY_UPDATE_INTERVAL。未宣告身分驗證。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Agency Mcp Server,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
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
來源:README.md,提交 e82d938
工具
0版本歷史
1- v0.2.2最新Sep 16, 2026
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