Structured Data Challenges

Observations that pure BM25 underperforms on tool outputs mixing JSON, tables, config with natural language, requiring hybrid approaches

To address the limitations of standard keyword search when dealing with mixed data formats, developers are shifting toward sophisticated retrieval and summarization strategies that go beyond simple text processing. Key innovations include the use of token-optimized dataframes to provide LLMs with concise summary views of massive datasets, alongside structured knowledge caches built on SQLite to make complex tool outputs more searchable. There is also a growing interest in evolving the Model Context Protocol (MCP) by transitioning from JSON to binary formats like Apache Arrow, which would enable agentic systems to process dense information more efficiently while reducing iterative query pressure.

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Very interesting, one big wrinkle with OP:s approach is exactly that, the structured responses are un-touched, which many tools return. Solution in OP as i understand it is the "execute" method. However, im building an MCP gateway, and such sandboxed execution isnt available (...yet), so your approach to this sounds very clever. Ill spend this day trying that out

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We do a fun variant of this for louie.ai when working with database and especially log systems -- think incident response, SRE, devops, outage investigations: instead of returning DB query results to the LLM, we create dataframes (think in-memory parquet). These directly go into responses with token-optimized summary views, including hints like "... + 1M rows", so the LLM doesn't have to drown in logs and can instead decide to drill back into the dataframe more intelligently. Less iterative query pressure on operational systems, faster & cheaper agentic reasoning iterations, and you get a nice notebook back with the interactive data views.

A curious thing about the MCP protocol is it in theory supports alternative content types like binary ones. That has made me curious about shifting much of the data side of the MCP universe from text/json to Apache Arrow, and making agentic harnesses smarter about these just as we're doing in louie.

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Nice approach. Same core idea as context-mode but specialized for your build domain. You're using SQLite as a structured knowledge cache over YAML rule files with keyword lookup. Context-mode does something similar but domain-agnostic, using FTS5 with BM25 ranking so any tool output becomes searchable without needing predefined schemas. Cool to see the pattern emerge independently from a completely different use case.

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