All servers · Documents & retrieval
io.github.nexus-mcp-infra/similarity-search-api-sdk
io.github.nexus-mcp-infra/similarity-search-api-sdk · v1.0.0
No registry update 90+ days
Measured by MCP Station
| Last check | Reachable |
|---|---|
| Checked at | — |
| Check success 7 / 30 days | — |
| First-try success 30 days | — |
| Median response | — |
| Lookups 30 days | — |
| Authentication | No auth |
| MCP version | 2025-06-18 |
| Rank score | — |
| Declared risk | Not declared (tools carry no read/destructive hints) |
| Capabilities declared | experimental, prompts, resources, tools |
| Tool definitions | 3 tools · with description 100% · input schema is an object 100% · read/destructive hints 0% |
Description written by the publisher, not verified
Stateless NMI + cosine fusion with entropy-driven alpha calibration
Connect
streamable-http · https://similarity-search-api-production.up.railway.app/mcp
claude mcp add --transport http similarity-search-api-sdk https://similarity-search-api-production.up.railway.app/mcp{
"mcpServers": {
"similarity-search-api-sdk": {
"url": "https://similarity-search-api-production.up.railway.app/mcp"
}
}
}Tools as reported by the server
nexus_similarity_search_api_rank_items_by_nmi_cosine_fusionRanks a corpus of items against a query vector using a calibrated fusion score (alpha * cosine + (1-alpha) * NMI_normalizado), where alpha is auto-derived from the corpus's marginal entropy unless overridden. Results are identified by their 0-indexed position in corpus_vectors (this tool does not acnexus_similarity_search_api_estimate_corpus_entropy_profileComputes the aggregate entropy-calibrated alpha for a corpus without running a full search -- useful to inspect before committing to a large rank_items_by_nmi_cosine_fusion call. Returns a single aggregate corpus_entropy value, NOT a per-dimension breakdown -- the real logic only exposes the mean manexus_similarity_search_api_score_pair_nmi_cosineComputes the NMI-cosine fusion score for exactly one (query, target) vector pair at a fixed alpha. Use for explainability, debugging, or unit-level validation of fusion scores before running full corpus ranking. Unlike corpus-level ranking, alpha is NOT auto-calibrated for a single pair -- the real
Repository · JSON · Text for agents · Registry updated 2026-07-17