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Matryoshka

Skill Documents & Content Early

MCP server for token-efficient large document analysis via the use of REPL state

121 starsApache-2.0 (commercial OK)FreeQuick setup
New Find — Recently discovered. Looks promising but has limited community feedback so far. We added it early so you can evaluate it before the crowd finds it.

Token budgets are the silent bottleneck in document-heavy AI workflows — Matryoshka uses REPL state to analyze documents that would otherwise blow past context limits, enabling real analysis instead of truncated summaries.

Analysts and researchers working with large PDFs, legal filings, or technical specs who need Claude to reason over entire documents without losing detail.

Claude Code Claude Cowork Claude Chat

https://github.com/yogthos/Matryoshka

By yogthos

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install yogthos/Matryoshka

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Automated Scan

Stars121Contributors4Last updated2026-04-12LicenseApache-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-04-13 · scanner v1

Community Pulse Active

Discussed on Hacker News, Reddit

21 mentions across 2 sources

Reviewer notes

Automated Scan review. These are observations, not a security certification.

Auto-evaluated from staging triage

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 EarlyEvaluatedApr 2026

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