Viewing enriched Twitter post
Does MCP Kill (Centralized) Vector Search? In the post-MCP world, AI agents will interact with the external world through MCP tools. There is a very valid question on whether you would want to have a centralized search index at all if agents can just directly interface with the… https://t.co/oEtREh6UVx
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"text": "Does MCP Kill (Centralized) Vector Search?\n\nIn the post-MCP world, AI agents will interact with the external world through MCP tools. There is a very valid question on whether you would want to have a centralized search index at all if agents can just directly interface with the tool interfaces (e.g. tool-call Jira, Salesforce, Notion).\n\nThe answer on whether you need a centralized index is actually quite nuanced 💡:\n✅ Yes for accurate and fast lookup of semantic context. Federated search is slow and relies on every third-party building their own search endpoints that don’t suck, which is unrealistic.\n\n✅ Yes for any document-based sources. There’s no native query interface for documents if they live in Sharepoint/Google Drive/S3. You would still need modules (e.g. through LlamaCloud) that would help you parse and index that data.\n\n🚫 No for deeper lookup within SaaS tools and action taking. AI agents can directly write JQL for Jira through the native MCP server - something that’s not possible through basic semantic search.\n\nI imagine in any agent architecture there’s both tools that enable accurate/cheap retrieval (centralized vector indexing), and tools that enable deeper interaction and manipulation (MCP tool wrappers over SaaS APIs)\n\nCheck out my blog here: https://t.co/s4VSQRTJG4",
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