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Connects AI assistants to Warpmetrics telemetry data to monitor AI agent performance, execution runs, and LLM costs. It allows users to query success rates, lat
Connects AI assistants to Warpmetrics telemetry data to monitor AI agent performance, execution runs, and LLM costs. It allows users to query success rates, latency, and spend metrics directly through natural language interfaces.
Connect AI assistants to your Warpmetrics AI agent telemetry via the Model Context Protocol.
npm install -g @warpmetrics/mcp
Create an API key at warpmetrics.com/app/api-keys
Add to your ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"warpmetrics": {
"command": "warpmetrics-mcp",
"env": {
"WARPMETRICS_API_KEY": "wm_live_your_api_key_here"
}
}
}
}
The Warpmetrics tools will now be available.
Tools are loaded dynamically from the Warpmetrics API and stay automatically in sync.
View all available tools:
npx @warpmetrics/mcp --list-tools| Variable | Required | Description |
|---|---|---|
WARPMETRICS_API_KEY |
Yes | Your Warpmetrics API key |
WARPMETRICS_API_URL |
No | API URL (default: https://api.warpmetrics.com) |
git clone https://github.com/warpmetrics/mcp.git
cd mcp
npm install
# Run locally
WARPMETRICS_API_KEY=wm_live_... node src/index.js
MIT
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"warpmetrics-mcp-server": {
"command": "npx",
"args": []
}
}
}Web content fetching and conversion for efficient LLM usage.
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also