trustscoreagent/trustscoreagent
by Various
Free, open reputation registry for AI microservices. Agents check trust scores before calling any service.
MCP
trustscoreagent/trustscoreagent
Added 3 Sept 2026
Overview
TrustScoreAgent is a free, open-source reputation registry for AI microservices, implemented in C#. It enables agents to query trust scores for services before invoking them, providing a decentralized mechanism for assessing service reliability.
Best for
Best for
Developers building AI agent systems that need a lightweight, open trust verification layer for microservices.
Use cases
- Allow AI agents to verify service trust scores before making API calls
- Publish and maintain reputation metrics for microservices in a shared registry
- Integrate trust checks into agent decision-making workflows for service selection
Notes
TrustScoreAgent is a free, open-source reputation registry for AI microservices, implemented in C#. It enables agents to query trust scores for services before invoking them, providing a decentralized mechanism for assessing service reliability.
0 stars on GitHub. Last updated 2026-08-30. Licensed Apache-2.0.
Use cases
- Allow AI agents to verify service trust scores before making API calls
- Publish and maintain reputation metrics for microservices in a shared registry
- Integrate trust checks into agent decision-making workflows for service selection
Pros
- Open source and free to use
- Built in C#, fitting .NET ecosystems
- Addresses a real need for trust in AI service interactions
Cons
- No current stars or community traction, indicating early-stage adoption
- Limited documentation and ecosystem support
- Reputation model may require significant customization for diverse use cases
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Open source and free to use
- Built in C#, fitting .NET ecosystems
- Addresses a real need for trust in AI service interactions
Cons
- No current stars or community traction, indicating early-stage adoption
- Limited documentation and ecosystem support
- Reputation model may require significant customization for diverse use cases
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