skills/install-agentpmt-mcp/SKILL.md
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, VS Code, Zed, OpenAI Codex CLI, Gemini CLI, or any MCP-compatible client to the AgentPMT tool marketplace. Also use when the user mentions AgentPMT setup, MCP server configuration, agent tool marketplace, or connecting an AI agent to paid tools and APIs.
npx skillsauth add AgentPMT/agent-skills install-agentpmt-mcpInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
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.
The user needs an AgentPMT account with:
If the user does not have these, direct them to create an account at https://www.agentpmt.com and set up a budget first.
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.
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.
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.
If automatic setup is not available or the user prefers manual configuration, follow the platform-specific instructions below.
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.
Claude Desktop
Edit the config file:
~/.config/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"agentpmt": {
"command": "npx",
"args": ["--package=@agentpmt/mcp-router@latest", "agentpmt-router"],
"env": {
"AGENTPMT_BEARER_TOKEN": "<your-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": "<your-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": "<your-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": "<your-base64-token>"
}
}
After saving the configuration, restart the AI client. The AgentPMT tools should appear in the tool list within a few seconds.
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 <base64-encoded-api_key:budget_key>
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer <your-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": {}
}
}'
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer <your-base64-token>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/list",
"params": {}
}'
curl -X POST https://api.agentpmt.com/mcp \
-H "Authorization: Bearer <your-base64-token>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "tool-name",
"arguments": { "param1": "value1" }
}
}'
Some clients (Claude Code, OpenAI agents) support remote MCP servers directly:
{
"mcpServers": {
"agentpmt": {
"url": "https://api.agentpmt.com/mcp",
"headers": {
"Authorization": "Bearer <your-base64-token>"
}
}
}
}
After setup, verify the connection works:
AgentPMT-Refresh-Tools and AgentPMT-Report-Tool-Issue confirm the connection is active.No tools appearing:
Authentication errors (401):
api_key:budget_key with a colon separatorTools listed but calls fail:
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.
tools
Plaud Transcripts Corrected With Your Own Terminology Glossary: Fixes the words your transcription keeps getting wrong, by giving the pipeline your vocabulary instead of hoping a bigger model guesses right. Every speech model mangles terms it has never seen: cell line and reagent names, drug and device names, case and matter numbers, part numbers, local spelling and number conventions, team and client names. Swapping to a different model does not fix this, because none of them have your terms e.
tools
Plaud Spoken Field Notes to a Structured Sheet: Turns a spoken site visit into a filled-in spreadsheet row, so measurements and specs never get typed up twice. Built for anyone who dictates structured details on the job rather than writing them down: window and flooring measurements, equipment specs, inspection findings, punch lists, service call notes. Say the details out loud in the same order each visit (client, room, width, drop, colour, notes) and the workflow reads each new Plaud recordin.
development
Plaud Recordings to Google Calendar Events: Puts the meetings you agree to out loud straight onto your Google Calendar, without Zapier in the middle. Plaud's own app has no Calendar integration, so this closes that gap directly: each new recording is scanned, the transcript pulled, and any genuine scheduling commitment spoken in it ("let's do Tuesday at 3", "I'll come back out Thursday morning") is extracted with the relative date resolved against the recording's own date and your timezone. Eac.
development
One Plaud Recording, Several Differently Formatted Summaries: Gets you past the one-template-per-recording ceiling. The Plaud app applies a single AutoFlow template to a recording, so if you want a short recap for yourself, a decisions-only version for the people who missed it, and a clean action list for your task manager, you are re-running or rewriting by hand. This workflow reads the transcript once and produces every format you have defined in a single pass: you list the output formats you.