MCP MeasureMCP Measure

index observed

ai·rete·rag

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

Should I use this

Quality & Safety

A
Description quality
98%
Schema completeness
70%
Naming quality
93%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~3,126Tokens (tool definitions)
~1.1 KBTypical response size
Significant attention impact (2.44% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "ai-rete-rag-mcp": {
      "command": "uvx",
      "args": [
        "ai-rete-rag-mcp"
      ]
    }
  }
}

Runnable packages

pypiai-rete-rag-mcp0.8.0stdio

Remote endpoints

https://ai-rete-rag.com/mcpstreamable-http
https://ai-rete-rag.com/mcp/authstreamable-http

What it can do

Tool inventory

No publishable tool enumeration has been recorded.

Community

Rate this Server

Evidence

Recent observations

failed observationversion not recorded—
verifiedversion not recorded9 tools
failed observationversion not recorded—
verifiedversion not recorded8 tools
verifiedversion not recorded8 tools