Graphify-Labs/graphify
Graphify transforms codebases, documentation, and other files into queryable knowledge graphs, enhancing developer productivity with local AST parsing and detailed edge explanations.
Awesome MCP › Software Development
Context Mode is a crucial MCP (Model Context Protocol) server solution addressing the inherent challenges of context window management for AI coding agents. It tackles four main problems: excessive context consumption from raw tool outputs, loss of session continuity, inefficient LLM utilization for data processing, and rigid prose-style enforcement. The server significantly reduces context window bloat by sandboxing tool outputs, achieving up to a 98% reduction in data sent to the LLM. For instance, a 315 KB raw output can be condensed to 5.4 KB. To maintain session continuity, Context Mode stores critical operational data (file edits, Git ops, tasks, errors, user decisions) in SQLite. Instead of re-injecting all historical data into the context, it indexes events using FTS5 and retrieves only relevant information via BM25 search, allowing the model to pick up exactly where it left off, even after conversation compaction. The project advocates for treating LLMs as code generators rather than raw data processors, enabling agents to write scripts that perform data analysis and output only consolidated results, drastically saving context tokens. Lastly, it ensures that while raw data is kept out of context, the LLM retains full control over its output style, preventing restrictive prompts that could degrade coding benchmarks. Context Mode integrates seamlessly with platforms like Claude Code, providing automatic routing enforcement and a suite of sandbox and meta-tools.
https://github.com/mksglu/context-mode
Graphify transforms codebases, documentation, and other files into queryable knowledge graphs, enhancing developer productivity with local AST parsing and detailed edge explanations.
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