0xDegenMo/lighter-mcp
by Various
0xDegenMo/lighter-mcp — indexed from awesome-mcp-servers-punkpeye
MCP
0xDegenMo/lighter-mcp
Added 1 June 2026
Overview
A lightweight Python implementation of a Model Context Protocol (MCP) server. It provides a minimal interface for serving context to AI models, sourced from the awesome-mcp-servers collection.
Best for
Best for
Developers exploring the Model Context Protocol who want a simple starting point
Use cases
- Integrating custom context into AI model workflows
- Prototyping MCP-based applications
- Learning the Model Context Protocol with a simple codebase
How to use
Install
pip install 0xdegenmo-lighter-mcp Tools exposed
LIGHTER_URLLIGHTER_ACCOUNT_INDEXLIGHTER_PRIVATE_KEYLIGHTER_API_KEY_INDEXLIGHTER_READ_ONLYLIGHTER_MAX_QUOTE_USDLIGHTER_MAX_SLIPPAGELIGHTER_ALLOWED_SYMBOLSLIGHTER_NO_INTEGRATORLIGHTER_INTEGRATOR_ACCOUNT_INDEXLIGHTER_INTEGRATOR_MAKER_FEELIGHTER_INTEGRATOR_TAKER_FEELIGHTER_MCP_LOG_LEVEL
Tested with
Claude Desktop, Cursor
Notes
A lightweight Python implementation of a Model Context Protocol (MCP) server. It provides a minimal interface for serving context to AI models, sourced from the awesome-mcp-servers collection.
1 stars on GitHub. Last updated 2026-05-28. Licensed MIT.
Use cases
- Integrating custom context into AI model workflows
- Prototyping MCP-based applications
- Learning the Model Context Protocol with a simple codebase
Pros
- Lightweight and minimal Python codebase
- Easy to understand and modify for experimentation
Cons
- Very early stage with only 1 star and limited community
- Minimal documentation and usage examples
- Unclear production readiness or ongoing maintenance
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Lightweight and minimal Python codebase
- Easy to understand and modify for experimentation
Cons
- Very early stage with only 1 star and limited community
- Minimal documentation and usage examples
- Unclear production readiness or ongoing maintenance
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
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