jinni MCP Server
smat-dev/jinni
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Bring your project into LLM context - tool and MCP server
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smat-dev/jinni is a Python MCP server licensed under Apache-2.0. Bring your project into LLM context - tool and MCP server
Ranked #8435 out of 24846 indexed tools.
Ecosystem
Python Apache-2.0
Score Breakdown
Stars 15% 274
274 stars → growing community
Freshness 25% 10mo ago
Last commit 10mo ago → stale
Issue Health 25% 80%
4/5 issues closed → responsive maintainer
Contributors 10% 3
3 contributors → small team
Dependents 25% 6
6 dependents → few downstream users
npm Downloads N/A
PyPI Downloads N/A
Forks 19
Description Good
License Apache-2.0
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
Description low impact
Freshness high impact
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[](https://agentrank-ai.com/tool/smat-dev--jinni/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) <a href="https://agentrank-ai.com/tool/smat-dev--jinni/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/smat-dev--jinni" alt="AgentRank"></a> Matched Queries
From the README
# Jinni: Bring Your Project Into Context
<a href="https://glama.ai/mcp/servers/@smat-dev/jinni">
</a>
Jinni is a tool to efficiently provide Large Language Models the context of your projects. It gives a consolidated view of relevant project files, overcoming the limitations and inefficiencies of reading files one by one. Each file's content is preceded by a simple header indicating its path:
```
```path=src/app.py
print("hello")
```
The philosophy behind this tool is that LLM context windows are large, models are smart, and directly seeing your project best equips the model to help with anything you throw at it.
There is an MCP (Model Context Protocol) server for integration with AI tools and a command-line utility (CLI) for manual use that copies project context to the clipboard ready to paste wherever you need it.
These tools are opinionated about what counts as relevant project context to best work out of the box in most use cases, automatically excluding:
* Binary fi Read full README on GitHub → Get the weekly AgentRank digest
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