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"Ray" matching MCP servers:

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    MCP Server for Raygun's API V3 endpoints for interacting with your Crash Reporting and Real User Monitoring applications. This server provides comprehensive access to Raygun's API features through the Model Context Protocol.
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    MIT
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    Christian Bible Scripture MCP: BSB verse lookup, Christian encouragement, the Doxa Way journey map. Three tools: doxa_encourage, doxa_scripture, doxa_way_movement. Hosted at https://doxa.app/mcp/v1, free per-individual quota, BYOL for unlimited. Scripture, summoned.
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    MIT
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    Enables AI agents to create cryptocurrency payments, check payment status, generate QR codes, and manage transactions through Bitnovo Pay API integration with automatic webhook support.
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    MIT
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    Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.
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    MIT
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    Official MCP server for Safefy, enabling AI agents to manage PIX payments, withdrawals, customers, and transactions via the Safefy payment API.
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    MIT
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    CP server for RAD Security, providing AI-powered security insights for Kubernetes and cloud environments. This server provides tools for querying the Rad Security API and retrieving security findings, reports, runtime data and many more.
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    MIT
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    A Model Context Protocol server for indexing and searching local document collections with hybrid BM25+vector search, optimized for Korean and English, supporting DOCX, PDF, audio, and more.
    MIT
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    Enables AI agents to send and receive USDC stablecoin payments on Base and Solana blockchains through MCP tools for wallet operations, balance checks, payment requests, and transfers.
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    MIT
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    Enables Pix payment operations (cash-in/cash-out) and webhook management for Intra Pay via natural language, supporting multi-tenant authentication.
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    Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.
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