Agency 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.

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:

Approach	Context cost	When
Installed agents (~/.claude/agents/)	~8,300 tokens	Every conversation, always
MCP server (idle)	~55 tokens	Every conversation
MCP server (searching)	~350 tokens	Only when you search
MCP server (using an agent)	~2,700 tokens	Only 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:

Division	Examples
Engineering	Software Architect, DevOps Engineer, Technical Writer
Design	UI Designer, UX Researcher, Design Systems
Game Development	Game Economy Designer, Game Mechanics Designer
Marketing	Content Strategist, SEO Specialist, Email Marketing
Security & Specialized	Security Auditor, Data Scientist, Legal Analyst
...and more	Academic, Sales, Strategy, Support, Testing, Spatial Computing

Configuration

All configuration is through environment variables in your MCP config:

Variable	Default	Description
AGENCY_AGENTS_PATH	~/.cache/agency-mcp-server/agency-agents	Path to agent templates. Set this to use your own templates instead of auto-cloning
AGENCY_REPO_URL	https://github.com/msitarzewski/agency-agents.git	Git repo to clone templates from. Point at your fork
AGENCY_AUTO_UPDATE	true	Set to false to disable automatic pulls
AGENCY_UPDATE_INTERVAL	24	Hours 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