Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.
- ai-agents
- claude-code
- mcp
- token-optimization
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Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Autonomous multi-agent framework to optimize scientific software
MCP server for spatial transcriptomics analysis through natural language interfaces.