"A server for finding customer, employee, and reviewer opinions on a company across the internet" matching MCP servers:

MCP server for securely connecting LLMs to customer data, providing customer profile retrieval, semantic search of interaction history, and exact financial summaries via SQL aggregation, with audit logging and prompt injection protection.

Provides MCP tools for retrieving customer records and processing refunds, with strict input validation, proper JSON-RPC error mapping, and enforced stdout protocol isolation.

Validates customer information completeness by checking caller-provided data against required fields, returning present and missing fields.

Enables querying customers by name with a React UI for pagination, details, external company search, and safe customer creation after explicit confirmation.

Enriches domains into full company profiles with firmographics and buying signals.

Enables Claude Desktop to answer natural-language questions about customers by exposing search, profile, order history, status filter, and spend statistics tools backed by local mock data, with a single-file swap path to Oracle AI Agent Studio later.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

Enables AI assistants to manage Customer Thermometer surveys, including listing thermometers and recipient lists, adding or unsubscribing recipients, sending email surveys, and retrieving NPS, happiness, response, and comment reports.

Enables reading campaign, segment, and message-delivery data from the Customer.io Journeys App API, including campaign metrics, audience segments, and recipient-level message outcomes.

Provides deterministic mock customer health, product usage, and recommended playbook data via three MCP tools for a Customer Success Orchestrator demo.

An MCP to give AI agents extensive knowledge of your personal finances and control of your budgeting.

An MCP adapter that maps Coffee Company B2B HTTP APIs to MCP tools, allowing AI agents to query member information, benefits, coupons, and payment statuses. It enables seamless integration for AI assistants to manage coffee-related customer assets and loyalty details through natural language.

Enables creating and managing customer records via an external API with Bearer token authentication, supporting required fields (name, email, phone) and extensive optional data including addresses, UTM parameters, and tags.

Provides read-only access to the Planning Center People API, enabling natural language queries for people, households, background checks, and lists.

Enables Claude to access and manage a travel company's customer data, trip history, and information requests. Supports searching customers, querying trips by destination or date, and tracking customer inquiries through natural language.

A server for interacting with the Iaptic API, allowing AI models like Claude to query customer, purchase, and transaction data, as well as retrieve statistical insights.

A Model Context Protocol server for Hatch API integration that provides tools for finding and verifying contact information including emails, phone numbers, LinkedIn profiles, and company data.

The VanMoof MCP Server implements the MCP specification to create a seamless connection between AI agents and key VanMoof services like VanMoof customer data, including bike details, VanMoof rider cities, rider preferences and weekly rides.

Production-ready MCP server enabling AI assistants to interact with Braze's customer engagement platform, offering 92 tools for user management, messaging, campaigns, analytics, email/SMS, catalogs, and SCIM provisioning.

Enables AI agents to interact with Salesforce CRM data by executing SOQL queries and managing records. It provides tools for object metadata discovery and record operations, specifically optimized for Heroku deployment.