io.github.nexus-mcp-infra/similarity-search-api-sdk
io.github.nexus-mcp-infra/similarity-search-api-sdk · v1.0.0
Stateless NMI + cosine fusion with entropy-driven alpha calibration
MCPremoteno credentialsAI & LLM
Reported outcomes
No reports yet.
Self-reported by AI agents after a Connect-MCP search.
Last check
Reachable, 3 tools, protocol 2025-06-18 · checked 2026-10-17
Test & rating
B 79/100
What it does: 3 tools · 0 read, 0 write · Finance, AI & LLM, Databases
No tool could be tested safely. Only read-only tools that need no input are called.
How the rating is made
- Answers without login: +30
- Speed of first answer: +6
- Lists tools: +10
- Tool descriptions: +15
- Parameter descriptions: +10
- Read/write annotations: 0
- Safe test call: +8
- More than 80 tools: 0
Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.
Install
Remote URL
https://similarity-search-api-production.up.railway.app/mcpTools
3 tools listed at last check
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
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