"A local vector-based search engine for personal documents" matching MCP servers:

In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.

A production-ready Model Context Protocol server that bridges local document management with cloud synchronization (Notion) for AI agent integration, enabling seamless access and sync of local and cloud documents.

Enables accurate Quranic verse search through natural language queries, returning exact text with no hallucinations.

Enables semantic search across indexed documents using vector embeddings. Index GitHub repositories and URLs to perform natural language queries with AI-enhanced contextual results.

Full-text search and retrieval over official congressional documents (hearings, committee reports, Congressional Record) with citations and govinfo.gov links, designed for grounding AI answers in the official record.

Gives multiple AI coding agents a shared, persistent memory by indexing your code and documentation into a vector database with AST-aware chunking and hybrid semantic/keyword search. Agents can search across projects and store, update, or forget decisions, conventions and lessons learned, all self-hosted with local embeddings.

Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.

Provides a free, no-paid-API web search gateway for AI agents using DuckDuckGo and Bing HTML scrapers, with tools for search, URL fetching, and text extraction.

Enables Google search queries and webpage content extraction through an MCP server deployed on Cloudflare Workers. Supports single and batch webpage content extraction with integrated OAuth authentication.

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.

A personal finance and business economics MCP server that provides math-backed answers to financial questions, including investment growth, loan amortization, debt payoff strategies, and tax estimation, all computed locally without API keys or network calls.

attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i

Enables agents to optimize and clean SVG vector paths, rasterize SVGs into crisp sub-pixel PNGs at custom DPI with alpha preserved, generate high-error-correction vector QR codes for payment URIs, and compress images to WebP while stripping EXIF metadata. Tools are metered via x402 USDC micropayments on Base L2.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Connects personal API integrations like Hevy fitness and exposes them as MCP tools, resources, and prompts.

Lets AI agents search and read your personal Telegram and WhatsApp conversations through a self-hosted, read-only MCP server backed by a single SQLite file.

Aggregates your digital footprint (GitHub, blogs, resume) into a single AI-readable profile and exposes it via MCP tools so AI agents can query your context live.