MCP Servers

MCP Agent Reliability Server

Logs tool call results, calculates reliability scores, and generates reports for AI agents, helping entrepreneurs measure agent reliability without paid APIs.

README

MCP Agent Reliability Server

Daily AI Project by Grok for Prince Ruhul / Prevalid
Date: 2026-07-29

What problem does this solve?

AI agents call tools all day. Sometimes they succeed, sometimes they fail silently.
Entrepreneurs and founders have no easy way to see "Is my agent actually reliable?"

This MCP server gives any AI agent (Claude, Cursor, Gemini, etc.) simple tools to:

Log every tool call result (success / fail + latency)
Calculate a live reliability score (0–100)
Generate a clear reliability report
Detect patterns of failure

All pure computation — no paid API required. Runs locally or on any serverless.

Quick Start

# Install
pip install -e .

# Run the MCP server (stdio)
python -m src.server

# Or with uv
uvx mcp-agent-reliability

Add to your Claude Desktop / Cursor MCP config:

{
  "mcpServers": {
    "agent-reliability": {
      "command": "python",
      "args": ["-m", "src.server"],
      "cwd": "/path/to/this/repo"
    }
  }
}

Tools exposed

Tool	Description
`log_tool_call`	Record a tool call outcome (name, success, latency_ms, optional error)
`get_reliability_score`	Get overall or per-tool reliability score (0-100)
`generate_reliability_report`	Full markdown report with scores, top failures, recommendations
`reset_stats`	Clear all logged data (for testing)
`list_tracked_tools`	See which tools have been logged so far

Why this is valuable for entrepreneurs

You can finally measure if your AI agent is production-ready
Agents can self-report their health before critical tasks
Zero cost — no external API keys needed
Works with the new stateless MCP (July 28 2026 update)

License

MIT

Built as part of the Daily AI Project series for Prevalid.

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