by yogthos · MCP Server · ★ 134
Matryoshka Process documents 100x larger than your LLM's context window—without vector databases or chunking heuristics. The Problem LLMs have fixed context windows. Traditional solutions (RAG, chunking) lose information or miss connections across chunks. RLM takes a different approach: the model reasons about your query and outputs symbolic commands that a logic engine executes against the document. Based on the Recursive Language Models paper.
| Stars | 134 |
| Forks | 16 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.43/100 |
| Last Updated | 2026-05-17 |
| Created | 2026-01-12 |
| Platforms | mcp, node |
| Est. Tokens | ~192k |
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Matryoshka is MCP server for token-efficient large document analysis via the use of REPL state. It is categorized as a MCP Server with 134 GitHub stars.
Matryoshka is primarily written in TypeScript. It covers topics such as ai-assistant, document-analysis, llm.
You can find installation instructions and usage details in the Matryoshka GitHub repository at github.com/yogthos/Matryoshka. The project has 134 stars and 16 forks, indicating an active community.
Matryoshka is released under the Apache-2.0 license, making it free to use and modify according to the license terms.