Install payload
Install payload is sparse; verify before rollout decisions.
33% (1/3)
Select entries to compare install and trust signals side by side.
3 results in this view
1 trust signal differs in this sample: Submitter
Signals differ on Submitter — add entries to compare before you install.
Rollout signal scan
Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.
Install payload
Install payload is sparse; verify before rollout decisions.
33% (1/3)
Most at-risk entries in this view
Adoption queue
2/3 visible results are in hold tier and need mitigation before adoption.
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
mcp/milvus-mcp-server · trust review · confidence 67%
2 blockers: Metadata review, Install payload
36/100
Request metadata review from maintainers or internal owners.
Add install/config payload for reproducible team rollout.
Collect package checksum or signed artifact information.
tools/gptcache · trust review · confidence 50%
2 blockers: Metadata review, Install payload
36/100
Request metadata review from maintainers or internal owners.
Add install/config payload for reproducible team rollout.
Collect package checksum or signed artifact information.
tools/milvus · trust review · confidence 50%
Decision confidence
2/3 results are low-confidence and need review before adoption.
Address Metadata review, Package integrity before broader rollout.
54/100
mcp/milvus-mcp-server · trust review
Hold adoption until Metadata review, Package integrity are resolved.
36/100
tools/gptcache · trust review
Hold adoption until Metadata review, Package integrity are resolved.
36/100
tools/milvus · trust review
Freshness distribution
Median age 45 days; all 3 scanned entries are within 90 days.
Theme distribution
67% of this view shares the top theme. Leading themes: retrieval, vector-database, cost-optimization.
9 distinct themes across 3 scanned
MCP server from Zilliz for connecting Claude to Milvus vector database collections, text search, vector search, hybrid search, inserts, deletes, indexes, collection loading, database switching, and collection metadata.
Apache-2.0 vector database for scalable ANN search, hybrid retrieval, RAG, recommendation systems, image search, multimodal search, and AI agent memory.
Open-source semantic cache for LLM applications that stores and reuses model responses through embedding similarity to cut API cost and latency, with modular embedding, vector-store, cache-storage, and eviction components.