{"repo":"ValkDB/dbdense","free":true,"listed":false,"github":"https://github.com/ValkDB/dbdense","clone":"git clone https://github.com/ValkDB/dbdense.git","description":"Offline database schema context for LLM agents. Extract once, serve via MCP — no live DB needed.","language":"Go","stars":13,"topics":["ai","database","mcp","utilities","tool","claude","developer-tools","golang","llm","model-context-protocol"],"license":"Apache-2.0","category":"mcp-servers","readme_excerpt":"dbdense - Schema context that fits in a prompt Most LLM questions only need a few tables, but tools send the whole schema. dbdense is an offline schema extraction and compile pipeline: it extracts your database schema once, builds a compact schema map, and renders detailed schema text on demand. It can also serve the result over MCP. The problem A 500-table schema is 93K tokens of DDL. Most questions touch 3-5 tables. Without schema context , the agent guesses at column names, misinterprets statuses, and burns tokens querying information schema to orient itself. With dbdense , a 4K token schema map stays in context. The agent sees every exported entity and FK relationship at a glance, then requests detailed schema text only for the objects it needs. In the current checked-in n=3 benchmark run (same model, same 5 questions, same seeded database): Metric Without schema context With dbdense Delta -------- ------------------------ -------------- ------- Correct answers 13/15 13/15 equal Avg turns 4.1 2.2 -46% fewer round-trips Avg total tokens per question 57,184 37,521 -34% fewer tokens Avg latency 34s 31s -8% faster Both arms achieved the same accuracy, but dbdense used 34% fewer total tokens per question and 46% fewer turns. The savings scale with query complexity: on multi-table joins, baseline spent up to 6 turns discovering schema while dbdense answered in 2. This run used precompiled schema DDL injected into the prompt, not the live MCP slice flow, and it still misses the ","default_branch":null,"files":null,"tree":[],"storefront":"/r/ValkDB","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ValkDB/dbdense/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}