/install install-agentpmt-mcp
Install AgentPMT MCP Server
Freshness
Last updated: 2026-06-03.
If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.
Connect any MCP-compatible AI agent to the AgentPMT tool marketplace. AgentPMT gives agents access to a dynamic catalog of tools, APIs, and services -- all controlled by budgets and spending limits.
Prerequisites
The user needs an AgentPMT account with:
- An API Key -- generated from Dashboard > Account > API Keys
- A Budget Key -- generated from Dashboard > Budgets > [Select Budget] > Budget Keys
If the user does not have these, direct them to create an account at https://www.agentpmt.com and set up a budget first.
Choose Installation Method
There are two ways to connect. Use the STDIO connector for desktop AI clients. Use the direct HTTPS endpoint for programmatic or web-based agents.
Method 1: STDIO Connector (Recommended for Desktop Clients)
This method uses the @agentpmt/mcp-router package, a lightweight local connector that routes MCP traffic to the AgentPMT cloud. It does not access local files or execute anything on the user's machine.
Automatic Setup
Run the interactive setup tool:
npm install -g @agentpmt/mcp-router
agentpmt-setup
The setup tool auto-detects installed AI platforms, prompts for credentials, writes the configuration files, and restarts the AI tools.
Manual Setup
If automatic setup is not available or the user prefers manual configuration, follow the platform-specific instructions below.
Step 1: Generate the Bearer Token
Combine the API key and budget key, then base64-encode them:
echo -n "YOUR_API_KEY:YOUR_BUDGET_KEY" | base64
This produces the Bearer token used in all configurations below.
Step 2: Configure the AI Client
Claude Desktop
Edit the config file:
- macOS:
~/.config/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"agentpmt": {
"command": "npx",
"args": ["--package=@agentpmt/mcp-router@latest", "agentpmt-router"],
"env": {
"AGENTPMT_BEARER_TOKEN": "\x3Cyour-base64-token>"
}
}
}
}
Claude Code
Add to the project's .mcp.json or the global ~/.claude/mcp.json:
{
"mcpServers": {
"agentpmt": {
"command": "npx",
"args": ["--package=@agentpmt/mcp-router@latest", "agentpmt-router"],
"env": {
"AGENTPMT_BEARER_TOKEN": "\x3Cyour-base64-token>"
}
}
}
}
Cursor
Add to Cursor's MCP settings (Settings > MCP Servers):
{
"mcpServers": {
"agentpmt": {
"command": "npx",
"args": ["--package=@agentpmt/mcp-router@latest", "agentpmt-router"],
"env": {
"AGENTPMT_BEARER_TOKEN": "\x3Cyour-base64-token>"
}
}
}
}
Windsurf, VS Code, Zed, and Other MCP Clients
Use the same universal configuration block. The only difference is where the config file lives for each client. The structure is always:
{
"command": "npx",
"args": ["--package=@agentpmt/mcp-router@latest", "agentpmt-router"],
"env": {
"AGENTPMT_BEARER_TOKEN": "\x3Cyour-base64-token>"
}
}
Step 3: Restart the AI Client
After saving the configuration, restart the AI client. The AgentPMT tools should appear in the tool list within a few seconds.
Method 2: Direct HTTPS Endpoint (For Programmatic Agents)
For agents that support remote MCP servers over HTTP, connect directly without the local connector.
Endpoint: https://api.agentpmt.com/mcp
Protocol: MCP 2.0 (JSON-RPC over streamable HTTP)
Authentication: Bearer token in the Authorization header.
Authorization: Bearer \x3Cbase64-encoded-api_key:budget_key>
Example: Initialize Connection
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer \x3Cyour-base64-token>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2025-03-26",
"clientInfo": { "name": "my-agent", "version": "1.0" },
"capabilities": {}
}
}'
Example: List Available Tools
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer \x3Cyour-base64-token>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/list",
"params": {}
}'
Example: Call a Tool
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer \x3Cyour-base64-token>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "tool-name",
"arguments": { "param1": "value1" }
}
}'
For Clients Supporting Remote MCP URLs
Some clients (Claude Code, OpenAI agents) support remote MCP servers directly:
{
"mcpServers": {
"agentpmt": {
"url": "https://api.agentpmt.com/mcp",
"headers": {
"Authorization": "Bearer \x3Cyour-base64-token>"
}
}
}
}
Verifying the Connection
After setup, verify the connection works:
- Ask the agent to list its available tools. AgentPMT tools should appear alongside any other configured tools.
- Look for built-in tools:
AgentPMT-Refresh-ToolsandAgentPMT-Report-Tool-Issueconfirm the connection is active. - Check the AgentPMT dashboard at https://www.agentpmt.com/dashboard -- active connections appear in real time.
Troubleshooting
No tools appearing:
- Verify the Bearer token is correctly base64-encoded (no trailing newlines)
- Confirm the budget has approved products -- tools only appear if the budget has vendors/products enabled
- Restart the AI client after saving config changes
Authentication errors (401):
- Regenerate the API key from the dashboard
- Ensure the budget key matches an active budget
- Check that the base64 encoding uses the format
api_key:budget_keywith a colon separator
Tools listed but calls fail:
- Check that the budget has sufficient credit balance
- Verify the specific product is approved for the budget
- Review the budget spending cap -- the agent cannot spend beyond the configured limit
How It Works
The AgentPMT MCP server dynamically assembles a tool catalog based on the budget's permissions. Each tool includes pricing metadata so the agent knows the cost before calling. Budget limits are enforced server-side. Every tool call is logged with a full audit trail visible in the dashboard.
The local STDIO connector (@agentpmt/mcp-router) is a thin relay. It does not access local files, does not execute code on the user's machine, and does not cache credentials beyond the current session. All tool execution happens on AgentPMT's cloud infrastructure.
Sessions expire after 2 hours of inactivity and are automatically refreshed on each request during active use.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install install-agentpmt-mcp - 安装完成后,直接呼叫该 Skill 的名称或使用
/install-agentpmt-mcp触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Install Agentpmt Mcp 是什么?
Install and configure the AgentPMT MCP server for any AI agent. Use this skill when the user wants to connect Claude Desktop, Claude Code, Cursor, Windsurf,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 27 次。
如何安装 Install Agentpmt Mcp?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install install-agentpmt-mcp」即可一键安装,无需额外配置。
Install Agentpmt Mcp 是免费的吗?
是的,Install Agentpmt Mcp 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Install Agentpmt Mcp 支持哪些平台?
Install Agentpmt Mcp 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Install Agentpmt Mcp?
由 AgentPMT(@agentpmt)开发并维护,当前版本 v1.0.0。