MCP server for depth-packed codebase context
A developer has created an MCP server that packs codebase context at 5 depth levels within a token budget. The tool addresses a specific problem: when Claude Code or other AI coding agents ask questions like "how does auth work?", they typically either load 3 files fully (missing the big picture) or get a flat repository map without actual content.
How it works
The server sits between these extremes, packing 40+ files at graded depth levels. The most relevant files are included at full content, while peripheral files are represented as just paths. This approach provides both breadth and depth within token constraints.
Three search modes
- Keyword mode: Free text search
- Semantic mode: Uses embeddings (~$0.0001 per query)
- Graph mode: Follows import relationships
These modes can be composed together for more sophisticated searches.
Technical implementation
The server uses AST parsing via tree-sitter and supports 14 programming languages. It provides several MCP tools:
packindex_workspaceindex_github_repobuild_embeddingsresolvestats
The tool is available on GitHub at https://github.com/victorgjn/agent-skills. The developer notes they haven't published the skill on skills.sh yet but plan to do so soon.
📖 Read the full source: r/ClaudeAI
👀 See Also
Testing MiniMax M2.7 via API on Three Real ML and Coding Workflows
A developer benchmarks MiniMax M2.7 against Claude Opus 4.7 on three real tasks: refactoring a PyTorch project, drafting Obsidian notes, and more. Key findings and setup included.
Claude 4.6 Opus Reasoning Distilled to 14GB for Apple Silicon via MLX Quantization
A developer has quantized a Qwen 3.5 27B model distilled from Claude 4.6 Opus reasoning trajectories from 55.6GB to 14GB using MLX for Apple Silicon, achieving ~16 tokens/sec on an M4 Pro while maintaining the model's analytical reasoning capabilities.
Open-source multi-agent framework extracted from Claude Code leak
A developer extracted the multi-agent orchestration system from Claude Code's leaked source code and rebuilt it as a model-agnostic open-source framework with MIT license. The 8,000-line TypeScript framework includes task scheduling, inter-agent messaging, and built-in tools.
Persistent Memory for Claude: Local Stack with MCP, 39ms Retrieval, 82% Token Reduction
A developer built a persistent memory layer for Claude using local vector search (Qdrant + Qwen3) and MCP integration, achieving 82% token reduction, 39ms hot-path retrieval, and session crystallization via L4 nodes.