MLQU 008 · Internal
Neocortex RAG
A retrieval platform an AI agent queries as a tool, not through another chat box.
FastAPIBedrockOpenSearchDynamoDBMCP
The problem
Most retrieval products end at a chat window, which means a human has to be the integration. What a team usually wants is for their own agent to reach into the corpus mid-task and keep going.
How it’s built
Ingest asynchronously
Uploads land in S3 and queue on SQS, so a large batch never blocks queries that are already running.
Embed and index
Bedrock Titan produces the vectors, OpenSearch holds them, and DynamoDB carries the metadata for filtering.
Expose it twice
A REST console with per-key scoping for people, and an MCP server for models, so any MCP client can use the corpus as a tool.
Front end
A Next.js console behind Cognito for uploading, browsing and managing API keys.
What changed
- Any MCP-capable agent can query the corpus without a bespoke integration
- Ingestion scales independently of query traffic
- Retrieval is a tool call rather than a person copying answers out of a chat window
Want one of these?
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