by yogthos · MCP Server · ★ 127
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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. How It Works Unlike traditional approaches where an LLM writes arbitrary code, RLM uses Nucleus—a constrained symbolic language based on S-expressions. The LLM outputs Nucleus commands, which are parsed, type-checked, and executed by Lattice, our logic engine. ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │ User Query │────▶│ LLM Reasons │────▶│ Nucleus Command │ │ "total sales?" │ │ about intent │ │ (sum RESULTS) │ └─────────────────┘ └─────────────────┘ └────────┬────────┘ │ ┌─────────────────┐ ┌─────────────────┐ ┌────────▼────────┐ │ Final Answer │◀────│ Lattice Engine │◀────│ Parser │ │ 13,000,000 │ │ Executes │ │ Valida
| Stars | 127 |
| Forks | 17 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.43/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-27 |
| Created | 2026-01-12 |
| Platforms | mcp, node |
| Est. Tokens | ~170k |
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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 127 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 127 stars and 17 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.
The top alternatives to Matryoshka on Agent Skills Hub include mcpproxy-go, mcp-nixos, agentql-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.