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docs(post-release): align README, server.json, package wrappers with v0.6.1
- README badges: languages 66->155, agents 10->11, tests 2586->2812 (actual count from v0.6.1 test run)
- README: VirusTotal table, primary VT badge link, all '66 languages' references, expanded language list with all newly added grammars
- server.json: bump 0.5.5->0.6.1 (was two releases behind), update all download URLs and sha256s
- pkg/scoop, homebrew, aur, chocolatey, winget: bump to 0.6.1 with new sha256s from v0.6.1 checksums.txt
- pkg/winget: new 0.6.1/ manifest directory (winget keeps version history; 0.6.0/ retained)
- pkg/npm/README: language and agent counts
**The fastest and most efficient code intelligence engine for AI coding agents.** Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a single static binary for macOS, Linux, and Windows — download, run `install`, done.
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High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across all 66 languages, enhanced with LSP-style hybrid type resolution for Go, C, and C++ (more languages coming soon) — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 10 coding agents.
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High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across all 155 languages, enhanced with LSP-style hybrid type resolution for Go, C, and C++ (more languages coming soon) — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 11 coding agents.
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> **Research** — The design and benchmarks behind this project are described in the preprint [*Codebase-Memory: Tree-Sitter-Based Knowledge Graphs for LLM Code Exploration via MCP*](https://arxiv.org/abs/2603.27277) (arXiv:2603.27277). Evaluated across 31 real-world repositories: 83% answer quality, 10× fewer tokens, 2.1× fewer tool calls vs. file-by-file exploration.
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-**Extreme indexing speed** — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline: LZ4 compression, in-memory SQLite, fused Aho-Corasick pattern matching. Memory released after indexing.
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-**Plug and play** — single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys. Download → `install` → restart agent → done.
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-**66 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
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-**155 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
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-**120x fewer tokens** — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search. One graph query replaces dozens of grep/read cycles.
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-**11 agents, one command** — `install` auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, OpenClaw, and Kiro — configures MCP entries, instruction files, and pre-tool hooks for each.
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-**Built-in graph visualization** — 3D interactive UI at `localhost:9749` (optional UI binary variant).
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## Language Support
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66 languages. Benchmarked against 64 real open-source repositories (78 to 49K nodes):
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155 languages, all parsed via vendored tree-sitter grammars compiled into the binary. Benchmarked against 64 real open-source repositories (78 to 49K nodes):
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**The fastest and most efficient code intelligence engine for AI coding agents.** Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a single static binary — this package downloads and runs it automatically.
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High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across 66 languages — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 10 coding agents.
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High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across 155 languages — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 11 coding agents.
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## Installation
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-**Extreme indexing speed** — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline with LZ4 compression and in-memory SQLite.
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-**Plug and play** — single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys.
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-**66 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
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-**155 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
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-**120x fewer tokens** — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search.
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-**10 agents, one command** — `install` auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, and OpenClaw.
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-**11 agents, one command** — `install` auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, OpenClaw, and Kiro.
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-**14 MCP tools** — search, trace, architecture, impact analysis, Cypher queries, dead code detection, cross-service HTTP linking, ADR management, and more.
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