{"id":5840,"date":"2025-04-28T17:51:28","date_gmt":"2025-04-28T15:51:28","guid":{"rendered":"https:\/\/onlu.ch\/mcp-agent-ai-the-ultimate-context-based-communication-platform-for-banks\/"},"modified":"2025-07-18T12:02:29","modified_gmt":"2025-07-18T10:02:29","slug":"mcp-agent-ai-the-ultimate-context-based-communication-platform-for-banks","status":"publish","type":"post","link":"https:\/\/onlu.ch\/en\/mcp-agent-ai-the-ultimate-context-based-communication-platform-for-banks\/","title":{"rendered":"MCP & Agent AI: The ultimate context-based communication platform for banks"},"content":{"rendered":"\t\t
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In today’s article, we look at how banks can implement a context-based communication platform<\/strong> based on the MCP principle. We summarize key requirements, market solutions and open source frameworks and compare them with LeapXpert (Swisscom) and Agentforce (Salesforce) as examples. <\/p>

<\/div>

1 Introduction: Why MCP and Agent AI are crucial for banks<\/h2>

Banks are under pressure to establish AI-driven<\/strong>, context-based<\/strong> communication platforms that work seamlessly across countries and channels. With Model Context Protocol (MCP)<\/strong> and Agent AI<\/strong>, existing APIs and integrations can be transformed into intelligent, agent-enabled services for next-best-action<\/strong>, automated summaries<\/strong> and real-time consent-based data processing<\/strong>. <\/p>

2 Central requirements for an MCP-capable communication platform<\/h2>

  1. Agent-based communication & Agent AI<\/strong><\/p>

    • AI agents (e.g. chatbots, virtual assistants) use context data for precise answers and actions.<\/p><\/li><\/ul><\/li>

    • Context-controlled workflows<\/strong><\/p>

      • Dynamic process control via DMN decision rules (e.g. channel selection, offer creation).<\/p><\/li><\/ul><\/li>

      • API orientation & MCP<\/strong><\/p>

        • Exposure of all backend systems via REST\/GraphQL APIs as MCP server.<\/p><\/li><\/ul><\/li>

        • Cross-channel collaboration<\/strong><\/p>

          • Standardized message and agent control via chat apps, e-mail, SMS, voice, video.<\/p><\/li><\/ul><\/li>

          • AI functions for banks<\/strong><\/p>

            • Next-best-action, automatic summaries, sentiment analysis.<\/p><\/li><\/ul><\/li>

            • Consent management<\/strong><\/p>

              • Strict adherence to consent in every customer interaction.<\/p><\/li><\/ul><\/li><\/ol>

                3. market overview: Commercial MCP & Agent AI platforms<\/h2>
                Solution<\/th>Core functions<\/th>Banking focus<\/th><\/tr><\/thead>
                MuleSoft MCP Support (Beta)<\/strong><\/td>APIs & integrations as MCP server, standardized agent-to-tool protocol, secure scaling<\/td>Enables AI agents next-best-action & real-time context<\/td><\/tr>
                LeapXpert<\/strong><\/td>Compliance chat in messaging apps, archiving, consent handling<\/td>Specialized chat compliance<\/td><\/tr>
                Symphony<\/strong><\/td>Secure multi-channel communication, bot\/API connection, AI summaries<\/td>Trading & Wealth Management<\/td><\/tr>
                Unblu<\/strong><\/td>Omnichannel (chat, video, co-browsing), secure messenger, AI co-pilot<\/td>Banks & insurers<\/td><\/tr>
                Qwil<\/strong><\/td>Cloud messenger with end-to-end encryption, file\/screen sharing<\/td>Banks, wealth management, law firms<\/td><\/tr>
                Infobip (CPaaS)<\/strong><\/td>SMS, WhatsApp, email, voice, chatbot builder, campaign workflows<\/td>Transaction notifications across all sectors<\/td><\/tr>
                Agentforce (Salesforce)<\/strong><\/td>Unified CRM platform, autonomous workflow management<\/td>Sales and service teams in banks<\/td><\/tr><\/tbody><\/table><\/div><\/div>

                4. open source frameworks for MCP & Agent AI<\/h2>
                Framework<\/th>Functions<\/th>Banking use<\/th><\/tr><\/thead>
                Rasa<\/strong><\/td>NLU, context-driven stories, multi-channel connectors, on-prem option<\/td>Chatbots, virtual assistants with agent AI function<\/td><\/tr>
                CIBSeven<\/strong><\/td>BPMN engine, DMN decision rules, banking connectors, on-prem performance<\/td>Orchestration of complex workflows & next-best-action<\/td><\/tr>
                MuleSoft Anypoint<\/strong><\/td>MCP connector, API management, integration templates<\/td>Seamless exposure of all systems as MCP servers for AI agents<\/td><\/tr><\/tbody><\/table><\/div><\/div>

                5. example architecture: MCP & Agent AI in banking operations<\/h2>
                <\/code><\/div>

                \"\"<\/p><\/div>

                1. Data Hub \/ Data Lake<\/strong><\/p>

                  • Saves customer profiles, consent records, event logs.<\/p><\/li>

                  • Provides context data (last contact, open opportunities) via REST\/GraphQL.<\/p><\/li><\/ul><\/li>

                  • CIBSeven BPMN & DMN<\/strong><\/p>

                    • Orchestrates “customer interaction” and “next-best-action” processes.<\/p><\/li><\/ul><\/li>

                    • Service APIs<\/strong><\/p>

                      • Consent service<\/strong>: Checks consent before interaction.<\/p><\/li>

                      • CRM service<\/strong>: Writes after-call summaries & NBX recommendations to the CRM.<\/p><\/li>

                      • NBX engine<\/strong>: Machine learning-based action suggestions.<\/p><\/li>

                      • MuleSoft MCP Server<\/strong>: Exposes MuleSoft APIs & integrations as MCP for Agent AI.<\/p><\/li><\/ul><\/li>

                      • Messaging gateway<\/strong><\/p>

                        • Delivery via LeapXpert, Infobip, Unblu, Qwil.<\/p><\/li><\/ul><\/li>

                        • Rasa Agent AI<\/strong><\/p>

                          • Uses Rasa NLU\/Stories for initial contact, forwards complex requests to agents.<\/p><\/li><\/ul><\/li>

                          • Monitoring & Audit<\/strong><\/p>

                            • Complete logging of all process instances, decisions, API calls in CIBSeven Cockpit.<\/p><\/li><\/ul><\/li><\/ol>

                              6 Conclusion: Flexibility & future-proofing thanks to MCP & Agent AI<\/h2>

                              With Model Context Protocol (MCP)<\/strong> and Agent AI<\/strong>, banks are creating a modular<\/strong>, context-driven<\/strong> and AI-enabled<\/strong> communication platform. The building block approach<\/strong> – from MuleSoft MCP and LeapXpert to Rasa and CIBSeven – allows next-best-action<\/strong>, compliance<\/strong> and omnichannel workflows<\/strong> to be optimally linked. So financial institutions are fit for the AI-native<\/strong> future! <\/p><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

                              Banks are increasingly looking for platform-independent communication solutions that function similarly to a Model Context Protocol (MCP). The focus here is on the following requirements: agent-based communication, context-driven workflows, API orientation, cross-channel collaboration, integration of AI functions (e.g. next-best-action, automatic summaries) and consent-based data processing. Both commercial solutions and open source frameworks that meet these criteria or can be extended to do so are presented below. Each solution is accompanied by information on functions, areas of application and a possible banking focus – including a brief comparison with LeapXpert where relevant. <\/p>\n","protected":false},"author":15,"featured_media":5592,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[85],"tags":[],"class_list":["post-5840","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-api-management"],"yoast_head":"\nMCP & Agent AI: The ultimate context-based communication platform for banks - ONLU AG<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/onlu.ch\/en\/mcp-agent-ai-the-ultimate-context-based-communication-platform-for-banks\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MCP & Agent AI: The ultimate context-based communication platform for banks - ONLU AG\" \/>\n<meta property=\"og:description\" content=\"Banks are increasingly looking for platform-independent communication solutions that function similarly to a Model Context Protocol (MCP). 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