Model Context Protocol (MCP) integration guide for connecting AI agents to Vouch reputation data and actions.
The Model Context Protocol (MCP) is an open standard developed by Anthropic for connecting AI systems to external data sources and tools. Vouch implements MCP to allow AI agents—including Claude, custom LLM applications, and workflow automation tools—to:
Vouch's MCP server exposes a set of tools and resources that AI agents can discover and invoke:
send_solicitation, draft_response, get_vouch_scoreThe MCP server runs as a separate service that authenticates requests using API keys scoped to specific tenants and permissions.
Step 1: Generate an API Key
From your Vouch dashboard, navigate to Settings → API Keys and create a new key with MCP access. Choose the appropriate scope (read-only, write, or admin).
Step 2: Configure Your MCP Client
Add the Vouch MCP server to your MCP client configuration. For Claude Desktop, edit your claude_desktop_config.json:
{
"mcpServers": {
"vouch": {
"command": "npx",
"args": ["-y", "@vouch/mcp-server"],
"env": {
"VOUCH_API_KEY": "your-api-key-here",
"VOUCH_API_URL": "https://api.tryvouch.io"
}
}
}
}Step 3: Test the Connection
In your MCP client, verify that Vouch tools are available by listing available tools or invoking a simple read operation like get_locations.
The Vouch MCP server exposes the following tools:
List all locations in the tenant with their review platform connections.
Query reviews by location, date range, rating, or platform. Supports filtering and pagination.
Retrieve the Vouch Score (composite reputation metric) for a location or tenant.
Trigger a review solicitation to a contact via email, SMS, or WhatsApp. Requires write permission.
Generate an AI-drafted response to a review. Returns draft text for human approval.
Post an approved response to a review platform. Requires write permission.
Retrieve AI-generated recommendations from the Recommendation Engine.
Query the audit log for compliance and troubleshooting. Requires admin permission.
Automated Reputation Reporting
An AI agent queries get_reviews and get_vouch_score weekly, generates a natural-language summary of reputation trends, and emails it to the management team.
Proactive Service Recovery
When a low-rated review is detected, an AI agent drafts a response using draft_response, flags it for manager approval, and creates a follow-up task in the CRM.
Multi-Location Benchmarking
An AI agent compares Vouch Scores across all locations, identifies underperformers, and suggests specific actions based on review themes and recommendation engine output.
Compliance Monitoring
An AI agent monitors the audit trail for consent violations, frequency cap breaches, or review gating patterns, and alerts the compliance team if anomalies are detected.
MCP API keys are scoped to specific permissions:
Keys can be further restricted to specific locations or date ranges. All MCP requests are logged in the audit trail.
MCP requests are subject to the following limits:
Contact support@aartha.ai if you need higher limits for production AI agent deployments.