"Using an AI Agent for Structured Search and Traversal in a Neo4j Database" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Automatically discovers vector indexes in a Neo4j database and exposes each as a semantic search tool with metadata pre-filtering, enabling natural language queries with dynamic filter support.

A self-hosted, MCP-native web-search backend for AI agents that provides meta-search, clean extraction, RAG with citations, and GitHub project selection.

Free multi-source search for AI agents with multi-source verification, token savings, and MCP native support.

Provides agent-friendly web search via MCP with zero-config free engines, region-aware failover, freshness filtering, and a one-call research tool that searches, fetches, and summarizes pages.

Enables MCP agents to perform native X (Twitter) searches with original-post citations and transparent usage tracking. Supports existing Grok login sessions or explicit xAI API billing without runtime dependencies.

Free multi-source web search server for AI agents, with confidence scoring and token optimization.

Provides a unified web search tool for AI agents by running multiple search providers concurrently and returning normalized results. It integrates with Claude Code, Codex CLI, OpenCode, and Hermes.

Read-only MCP server for discovering and ranking on-chain agents on Stellar mainnet via natural language search, reputation probes, and profile lookups.

An MCP server that enables Claude Code to perform web searches via Bing, read webpage content, and get current time, with a smart search skill for structured multi-source verification.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

Enables agents to run free-first English and Chinese web searches without API keys, returning compact multi-source evidence with visible provider failures and bounded request and evidence budgets. Optional paid providers can be used under routing policy when configured.

ai-jobs-agent MCP server: Exposes an autonomous job-detection agent's data to MCP clients, offering tools to search jobs, retrieve job details, view detection-latency statistics, and trigger on-demand sweeps

Enables English and Chinese web search that starts working with zero API keys, returning compact multi-source evidence with provenance, visible provider failures, and bounded request and evidence budgets. Optional paid providers run only when routing policy and credentials allow, and results can be fetched as clean Markdown from supported sources.

Enables free-first web search in English and Chinese with no API key required, returning compact multi-source evidence while keeping provider failures, stop reasons, and budget limits visible. Optional paid providers are used only when routing policy and credentials allow.

Enables English and Chinese web search through zero-key sources, plus optional paid providers under an explicit routing policy, without requiring an API account to start. Returns compact multi-source results that preserve provenance, provider failures, and bounded evidence budgets so agents can inspect how each result was found.

Enables an AI agent or any MCP host to discover and call keyless web search, safe arithmetic, constrained HTTP fetching, and current-time tools over stdio, with model tool-calling powered by Groq's free API or local Ollama.

Enables English and Chinese web search without an API key, returning compact multi-source evidence with provenance, visible provider failures, and bounded request and evidence budgets, while optionally using paid providers under an explicit policy.