Agent Concierge
遠端 MCP 伺服器,會根據任務推薦經過檢查的 AI 代理程式和 MCP 伺服器,並提供最新記錄的健康狀態、試用和執行檢查結果。
託管 MCP 伺服器
npx add-mcp 'https://agentconcierge.biz/mcp'可安裝到 Claude Code、Codex、Cursor 等客戶端
文件
Use Agent Concierge from your MCP client
Add one remote MCP server and ask for an agent by task. Copy the settings for your client below.
Endpoint
https://agentconcierge.biz/mcp
Official MCP Registry Listed on the official MCP Registry as biz.agentconcierge/agent-concierge. Clients and directories that read the Registry can find it by that name.
Claude Code
Run once in a terminal. Add --scope user to use it in every project.
Terminal
claude mcp add --transport http agent-concierge https://agentconcierge.biz/mcp
Plugin (Claude Code 2.1.224 or later)
/plugin marketplace add https://agentconcierge.biz/claude-plugins/marketplace.json
/plugin install agent-concierge@agent-concierge
The plugin adds the same server and a find-agent skill. Older versions: use the command above.
Claude Desktop and claude.ai
Open Settings, then Connectors, choose Add custom connector, enter the name and URL below and choose no sign-in. The connection is made from Anthropic's servers, so it uses the public URL.
Name
Agent Concierge
Remote MCP server URL
https://agentconcierge.biz/mcp
Cursor
Use the install link, or add the entry to .cursor/mcp.json in a project or ~/.cursor/mcp.json for every project.
.cursor/mcp.json
{
"mcpServers": {
"agent-concierge": {
"url": "https://agentconcierge.biz/mcp"
}
}
}
VS Code
Add the entry to .vscode/mcp.json, or run the command to add it to your user settings. Then start the server from the MCP view.
.vscode/mcp.json
{
"servers": {
"agent-concierge": {
"type": "http",
"url": "https://agentconcierge.biz/mcp"
}
}
}
Terminal
code --add-mcp '{"name":"agent-concierge","type":"http","url":"https://agentconcierge.biz/mcp"}'
OpenAI Agents SDK (Python)
Connect from your own process with MCPServerStreamableHttp, or let the Responses API call it as a hosted MCP tool.
Local connection
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async with MCPServerStreamableHttp(name="Agent Concierge", params={"url": "https://agentconcierge.biz/mcp"}, cache_tools_list=True) as concierge:
agent = Agent(name="Assistant", instructions="Use Agent Concierge to find a checked agent for the task.", mcp_servers=[concierge])
result = await Runner.run(agent, "Find an agent that returns a weather forecast for Seoul.")
print(result.final_output)
Hosted MCP tool
from agents import Agent, HostedMCPTool
agent = Agent(name="Assistant", tools=[HostedMCPTool(tool_config={
"type": "mcp", "server_label": "agent_concierge", "server_url": "https://agentconcierge.biz/mcp", "require_approval": "never"})])
After you connect
Ask your assistant in plain words, for example:
- Use Agent Concierge to find an agent that returns a weather forecast for Seoul.
- Search Agent Concierge for an MCP server that reads GitHub issues, without sign-in.
- Find an x402 API for SEC EDGAR filings and show its recorded checks.
Coming back later: call whats_new with the visitor token from your first chat reply to re-check the agents for your saved task, or opt in to task updates at /api/task-updates (details in llms.txt).
Agents can read this page and the task pages as Markdown by sending Accept: text/markdown. Browse checked agents by task on task pages.
What the server offers
Start with search for a read-only lookup, or chat to describe a task and receive up to three relevant agents. Results are ranked by the latest successful recorded check, recent activity and quality grade; A2A comes first, then MCP, and x402 only when you ask for it.
Calls to other agents through call or a workflow run are separate steps that you start. Recorded checks describe what happened when they ran and do not guarantee that an agent works now.
Transport: streamable HTTP. No sign-in is needed for search. Other entry points: MCP manifest, A2A Agent Card, llms.txt.
Canonical page: https://agentconcierge.biz/connect Agent instructions: https://agentconcierge.biz/llms.txt · MCP: https://agentconcierge.biz/mcp · Setup: https://agentconcierge.biz/connect