Groundcontrol

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Empowers AI coding agents with a pure Rust Model Context Protocol server, offering sub-millisecond, multi-modal knowledge retrieval to combat context exhaustion and reasoning rot.

Groundcontrol is a pure Rust Model Context Protocol (MCP) server specifically designed to address the critical challenges of context exhaustion and reasoning rot faced by modern AI coding agents. It unifies polyglot AST code chunking, full-text Tantivy BM25, local ONNX dense vectors, and typed graph traversal into a sub-millisecond, multi-modal retrieval engine. By implementing a strict 3-Tier Progressive Disclosure model, Groundcontrol enables agents to receive precise answers in a single round-trip, leading to significant token savings and more reliable, deterministic grounding in code and documentation.

Key Features

01Bi-modal retrieval across code and documentation with 3-way Reciprocal Rank Fusion (RRF).
02Cypher-Lite pattern queries (`graph_match`) compiled to recursive SQLite CTEs for intuitive graph traversal.
030 GitHub stars
04Sub-millisecond hybrid BM25 + ONNX vector + AST knowledge graph retrieval with 3-tier progressive disclosure.
05100% deterministic knowledge graph built from Tree-sitter AST relationships, frontmatter, and wikilinks.
06Pure Rust implementation with zero C-dependencies, ensuring high performance and reliability.

Use Cases

01Grounding AI coding agents in a deterministic, up-to-date knowledge base of code and documentation.
02Reducing token consumption and improving reasoning accuracy for LLMs by providing precise, tiered context.
03Serving as a high-concurrency shared memory layer across specialized agent swarms for collaborative tasks.