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MCP servers and skills: search, filter by where they run, and compare.
redis-vl-pythonredis
LocalRedis Vector Library. The AI-native Python client for Redis.
OfficialPythonMIT★ 432No key
MCP servers and skills: search, filter by where they run, and compare.
Redis Vector Library. The AI-native Python client for Redis.
OfficialPythonMIT★ 432No key
Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid sear
OfficialSkillApache-2.0★ 21k in collectionNo key
Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'BM25 or sparse vectors?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from
OfficialSkillMIT★ 40k in collectionNo key
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect o
OfficialSkillApache-2.0★ 21k in collectionNo key
Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python, TypeScript, Rust, Go,
OfficialSkillApache-2.0★ 257No key
Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of you
OfficialSkillMIT★ 40k in collectionNo key
Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact',
OfficialSkillMIT★ 40k in collectionNo key
Use Redis over HTTP from serverless and edge runtimes with @upstash/redis, and add rate limiting with @upstash/ratelimit. Use when the user mentions Upstash Redis, needs Redis from a Next.js route han
OfficialSkillMIT★ 40k in collectionNo key
An official Qdrant Model Context Protocol (MCP) server implementation
OfficialPythonApache-2.0★ 1.5kNo key
Diagnoses and fixes slow Qdrant indexing and data ingestion. Use when someone reports 'uploads are slow', 'indexing takes forever', 'optimizer is stuck', 'HNSW build time too long', or 'data uploaded
OfficialSkillMIT★ 40k in collectionNo key
Practical MCP server for large BigQuery datasets. Supports vector search. Keep LLM context small while staying fast and allowing only safe read-only actions.
PythonMIT★ 10No key
All-in-one platform for search, recommendations, RAG, and analytics offered via API
SkillMIT★ 2.7kNo key
A Model Context Protocol (MCP) server implementation that provides database capabilities for Chroma
OfficialPythonApache-2.0★ 600No key
Rust graph-vector database: OpenCypher (99.9% of evaluated TCK scenarios pass), vector search, graph algorithms, RESP + HTTP. LDBC SNB Interactive and BI complete; 1B edges on one machine.
SkillApache-2.0★ 184No key
Expanding the candidate pool via relevance feedback, as an alternative to reranking when a dense retriever is too weak. Use when someone asks about 'Qdrant's Relevance Feedback API', 'improving dense
OfficialSkillApache-2.0★ 256 in collectionNo key
Python toolkit for building graph-enhanced GenAI applications
OfficialSkillApache-2.0★ 449No key
Use the official MongoDB Skills with your favorite coding agent to build faster.
OfficialSkillApache-2.0★ 190No key
Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're ther
OfficialSkillApache-2.0★ 256 in collectionNo key
Constructing prefetch queries for hybrid retrieval, including sparse/dense and multi-field setups, and choosing a sparse embedding model. Use when someone asks 'dense and sparse in one search?', 'how
OfficialSkillApache-2.0★ 256 in collectionNo key
A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.
PythonApache-2.0★ 4.5kNo key
Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or
OfficialSkillApache-2.0★ 256 in collectionNo key
Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-fl
Node.jsAGPL-3.0★ 3.3kNo key
Turn your Readwise library into a blazing-fast, self-hosted semantic search engine – complete with nightly syncs, vector search API, Prometheus metrics, and a streaming MCP server for LLM clients.
PythonMIT★ 24No key
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