"Historical Cryptocurrency Data and Sector Trend Analysis" matching MCP servers:

Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Indexes local files (PDF, TXT, CSV, Markdown) with embeddings for semantic search. Provides both CLI and MCP server interfaces so Claude Desktop can search and read your local documents.

An MCP server that analyzes Python codebases using AST, stores code elements in a vector database, and enables natural language queries about code structure and functionality using RAG with Google's Gemini models.

A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.

Enables RAG-based querying of local stock company data using a local LLM and vector database, providing tools to ask questions, search raw chunks, and list documents.

Enables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.

Enables LLM hosts to retrieve live, relevant documentation excerpts from official library docs sites via a search-and-RAG tool, avoiding reliance on training data.

Semantic search over Nordic economic data — market announcements, quarterly reports (162 companies), macro data (NO/SE/DK/FI), commodity prices, and press releases. 180,000+ vectors.

Enables Claude to scrape, crawl, extract data, and sync to vector databases using scrapedatshi's RAG pipeline, with support for multiple embedding and vector DB providers.

Enables answering Formula 1 FAQ questions via vector search and web search using Bright Data.

An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.

RAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.

A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.

Enables Claude Desktop to search, add, list, retrieve, reinforce, and delete memories through a remote HTTP memory API, with hierarchical sector classification such as episodic, semantic, and procedural. It also supports connectivity health checks and optional API key authentication for the backing graph and vector store.

Connects AI agents to Teradata databases for querying, analysis, administration, and AI pipelines with enterprise security.

An MCP server for aggregating multi-domain intelligence feeds, performing 80:20 crossover analysis, and publishing structured insights to multiple channels.

A Model Context Protocol server for Chroma, enabling AI models to create collections and retrieve data using vector search, full text search, and metadata filtering.

An MCP server that streams K-line (candlestick) data from decentralized exchanges (DEXs) to power your AI agents and workflows.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.