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jacobsd32-cpu/djd-agent-score-mcp

by Various

MCP server for DJD Agent Score — reputation scoring tools for AI assistants

J

MCP

jacobsd32-cpu/djd-agent-score-mcp

Added 1 June 2026

#ai-agents #base #blockchain #mcp #mcp-server #model-context-protocol #reputation #wallet-scoring

Overview

An MCP server that exposes reputation scoring tools for AI assistants using DJD Agent Score. Built in TypeScript, it provides a standard interface for querying or updating agent reputation metrics via the Model Context Protocol.

Best for

Best for
Developers experimenting with agent reputation systems in MCP-based architectures

Use cases

  • Integrating reputation scoring into MCP-enabled AI assistants
  • Building trust metrics for multi-agent systems
  • Tracking and evaluating AI assistant behavior over time

Notes

An MCP server that exposes reputation scoring tools for AI assistants using DJD Agent Score. Built in TypeScript, it provides a standard interface for querying or updating agent reputation metrics via the Model Context Protocol.

0 stars on GitHub. Last updated 2026-03-06. Licensed MIT.

Use cases

  • Integrating reputation scoring into MCP-enabled AI assistants
  • Building trust metrics for multi-agent systems
  • Tracking and evaluating AI assistant behavior over time

Pros

  • Open-source TypeScript implementation with a standard MCP interface
  • Lightweight and focused on reputation scoring for agents
  • No external dependencies beyond the MCP protocol

Cons

  • Zero stars on GitHub indicates minimal adoption or community validation
  • No documentation beyond the one-line description
  • Scoring logic is opaque and may lack robustness for production use

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open-source TypeScript implementation with a standard MCP interface
  • Lightweight and focused on reputation scoring for agents
  • No external dependencies beyond the MCP protocol

Cons

  • Zero stars on GitHub indicates minimal adoption or community validation
  • No documentation beyond the one-line description
  • Scoring logic is opaque and may lack robustness for production use
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