AI tech lead for coding agents with validation and impact analysis
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
An intelligent MCP server that acts as an AI tech lead for coding agents—providing expert validation, impact analysis, and strategic guidance before code changes are made. Like a senior engineer reviewing your approach, Athena Protocol helps AI agents catch critical issues early, validate assumptions against the actual codebase, and optimize their problem-solving strategies. The result: higher quality code, fewer regressions, and more thoughtful architectural decisions.
Key Feature: Precision file analysis with analysisTargets - achieve 70-85% token reduction and 3-4× faster performance with precision-targeted code analysis. See Enhanced File Analysis for details
Imagine LLMs working with context so refined and targeted that they eliminate guesswork, reduce errors by 80%, and deliver code with the precision of seasoned architects—transforming how AI agents understand and enhance complex codebases.
This server handles API keys for multiple LLM providers. Ensure your .env file is properly secured and never committed to version control. The server validates all API keys on startup and provides detailed error messages for configuration issues.
The Athena Protocol MCP Server provides systematic thinking validation for AI coding agents. It supports 14 LLM providers and offers various validation tools including thinking validation, impact analysis, assumption checking, dependency mapping, and thinking optimization.
Key features:
This module depends upon a knowledge of Node.js and npm.
The Athena Protocol uses 100% environment-driven configuration - no hardcoded provider values or defaults. Configure everything through your .env file:
Edit .env and configure your provider:
DEFAULT_LLM_PROVIDER (e.g., openai, anthropic, google)Validate and test:
See .env.example for complete configuration options and all 14 supported providers.
PROVIDER_SELECTION_PRIORITY is REQUIRED - list your providers in priority order.envThe Athena Protocol supports 14 LLM providers. While OpenAI is commonly used, you can configure any of:
Major Cloud Providers:
Specialized Providers:
Local/Self-Hosted:
Quick switch example:
See the detailed provider guide for complete setup instructions.
For detailed, tested MCP client configurations, see CLIENT_MCP_CONFIGURATION_EXAMPLES.md
Local installation with .env file remains fully functional and unchanged. Simply clone the repository and run:
Then configure your MCP client to point to the local installation:
For npm/npx usage, configure your MCP client with environment variables. Only the configurations in CLIENT_MCP_CONFIGURATION_EXAMPLES.md are tested and guaranteed to work.
Example for GPT-5:
See CLIENT_MCP_CONFIGURATION_EXAMPLES.md for complete working configurations.
Configuration Notes:
npx @n0zer0d4y/athena-protocol with the env field for easiest setup.env file execution remains fully functional and unchangedenv variables take precedence over .env file variablesLLM_TEMPERATURE_DEFAULT, LLM_MAX_TOKENS_DEFAULT, and LLM_TIMEOUT_DEFAULT are currently required for GPT-5 models but are not used by the model itself. This is a temporary limitation that will be addressed in a future refactoringCurrent Issue: GPT-5 models currently require the standard LLM parameters (LLM_TEMPERATURE_DEFAULT, LLM_MAX_TOKENS_DEFAULT, LLM_TIMEOUT_DEFAULT) even though these parameters are not used by the model.
Planned Solution:
getTemperature() function to return undefined for GPT-5+ models instead of a hardcoded defaultundefined temperature valuesBenefits:
Timeline: Target implementation in v0.3.0
Athena Protocol supports 14 providers including:
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