context-rot-detection

MCP service that gives AI agents self-awareness about their cognitive state.

Every long-running AI agent suffers from context rot — measurable performance degradation as the context window fills up. Research from Chroma, Stanford ("lost-in-the-middle"), and Redis confirms this is the #1 practical failure mode in production agent systems.

An agent experiencing context rot doesn't *know* it's degrading — it just starts making worse decisions. This tool gives agents real-time visibility into their own cognitive health.

• Health score (0–100) based on token utilization, retrieval accuracy, and session fatigue
• Model-specific degradation curves for 15+ curated models (Claude, GPT, Gemini, o-series)
• Auto-resolves any HuggingFace model — pass a repo ID like meta-llama/Llama-3.1-70B and the context window is detected automatically, with results cached in SQLite
• Lost-in-the-middle risk scoring based on Stanford research
• Tool-call burden and session fatigue analysis
• Actionable recovery recommendations — compact context, offload to memory, checkpoint, break into subtasks
• Per-agent health history tracking (SQLite)
• Service-wide utilization statistics

npx context-rot-detection

npm install -g context-rot-detection
context-rot-detection

Add to .mcp.json in your project root:

{
  "mcpServers": {
    "context-rot-detection": {
      "command": "npx",
      "args": ["-y", "context-rot-detection"],
      "env": {
        "HEALTH_HISTORY_DB": "./health.db"
      }
    }
  }
}

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "context-rot-detection": {
      "command": "npx",