"Vite" matching MCP servers:

Enables LLMs to explore database schemas, execute read-only SQL queries, and perform data analysis on Apache Doris or MySQL-compatible databases through a standardized MCP interface with built-in analytical prompts.

Returns verified financial data (SEC EDGAR & FRED) with machine-readable citations. Guaranteed zero hallucinations for AI agents.

Provides ephemeral hybrid (vector + BM25) memory for MCP-compatible editors, enabling AI to save and search conversation and code context across sessions with automatic semantic search and context injection.

An MCP server for Claude Code that enables semantic search of past session transcripts and intelligent session forking, allowing users to find and resume from relevant previous conversations with full context.

Automatically synchronizes meeting transcripts from Otter.ai to a local SQLite database for easy browsing and management. It enables semantic and keyword-based search across meeting history through integrated MCP tools for Claude and Cursor.

A lightweight, dependency-free MCP server that answers cited queries over a Tero corpus index.json via stdio JSON-RPC 2.0, with honest refusal semantics and no silent empty results.

An offline-first, governed memory and knowledge server for AI agents that provides Remember, Search, Update, and Forget operations with hybrid retrieval, semantic embeddings, and NID-based authentication. It can be used as an MCP server via stdio or Streamable HTTP, enabling agents to persist and query memories and wiki knowledge.

Enables AI assistants to search a local paper library, find evidence for claims, and generate citations only for papers actually held in the library.

Turns any website URL into a crawled markdown corpus and knowledge graph, then exposes it to AI agents over MCP. Enables full-text search, full page retrieval, subgraph neighbor expansion, and site statistics so agents can answer questions grounded in a specific site's documentation.

Local MCP server to index your codebase once and search it across AI sessions with keyword, semantic, or hybrid search, keeping all data on disk.

An MCP server that gives Claude Code persistent, fully local long-term memory across conversations, with tools to query, log, consolidate, snapshot, and delete memories without any LLM calls.

Enables a self-hosted AI workspace with persistent sessions, agent run/step execution logs, unified search across conversations and knowledge, and discovery/invocation of local and remote MCP tools.

Enables AI assistants to search through structured databases and unstructured content (documents, videos, files) using natural language queries with semantic understanding.

Crawls a website, indexes its content, and answers questions with cited sources over MCP.

Enables minimal interaction with Supabase databases through 4 essential tools for data querying, mutations, file storage, and user authentication. Designed for 70% less context usage than standard implementations with auto-truncated results and simplified parameters.