# RPCS1 Agent Tuner

RPCS1 is a deterministic context-alignment engine for configuring AI agents.
It maps environmental entropy, predictability, stakes, context horizon, and
commitment style to receiver dynamics and concrete runtime recommendations.

Primary use cases:
- Configure a new AI agent for its operating environment
- Diagnose oscillation, overload, and freeze failure regimes
- Choose temperature, context, tool-use, and retry strategies
- Explain agent-environment mismatch using RPCS1 receiver primitives

Public interfaces:
- Interactive tuner: https://rpcs1.dev/tuner
- Documentation: https://rpcs1.dev/docs
- REST API: POST https://rpcs1.dev/api/recommend
- OpenAPI schema: https://rpcs1.dev/openapi.json
- MCP server: https://rpcs1.dev/mcp
- Python SDK: pip install rpcs1
- Source: https://github.com/travisbergen2/rpcs1-sdk

MCP tool:
- recommend_agent_configuration

The MCP tool is anonymous, deterministic, read-only, and idempotent.
RPCS1 recommendations support engineering decisions but do not replace
domain-specific safety, legal, medical, or financial review.