py-xiaozhi
Open-source AI assistant ecosystem with MCP integrations, multimodal workflows, IoT support, and cross-platform voice interaction.
Is py-xiaozhi safe? Thin or incomplete trust evidence. Review carefully before production use.
Compare py-xiaozhi
How does it stack up against its Voice & Conversational neighbours?
Pick any agent to compare →In detail: py-xiaozhi scores 47.7/100 (Grade D), ranked #1004 of 1325 tracked open-source AI agent projects, on evidence coverage C (2 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 2.1/10; 7% of recent commits are signed; last pushed 2026-09-11. Every point is earned from checkable signals — never paid placement. How scoring works →
How py-xiaozhi compares in Voice & Conversational
- #9 MaiBot 56.0 +8.3
- #10 Bolna 55.9 +8.2
- #11 py-xiaozhi 47.7 this agent
- #12 Call Center AI 44.9 −2.8
- #13 open-claude-tag 36.0 −11.7
Bars show each HVTrust score; the tick marks py-xiaozhi’s 47.7.
Where the 47.7 comes from
HVTrust dimensions vs the Voice & Conversational average
47.7 / 100 · 100.0% confidencepy-xiaozhi Voice & Conversational average (13 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade D reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage C is separate — it grades how many independent signal types back the score (2 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
64.9 / 100Supply Chain Trust
Common questions about py-xiaozhi
Does py-xiaozhi publish package provenance?
Does py-xiaozhi have an OpenSSF Scorecard?
Is py-xiaozhi actively maintained?
What license does py-xiaozhi use?
Are py-xiaozhi's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to py-xiaozhi's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.
Maintain py-xiaozhi?
For maintainers
HVTrust scores py-xiaozhi from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/py-xiaozhi)
<a href="https://hvtracker.net/agents/py-xiaozhi"><img src="https://hvtracker.net/badge/py-xiaozhi.svg" alt="HVTrust"></a>
Other agents in Voice & Conversational
GitHub REST API (repo, commits, stars, forks, license) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.3 · Raw JSON