"Discover" matching MCP servers:

Enables coding agents to run disciplined hunts over public data, enforcing evidence ledgers, calibration controls, novelty checks against catalogues and literature, and fresh-eyes review before any claim is trusted. Human-only decisions such as waivers and expert attestations stay out of reach of the agent.

Enables AI assistants to search and explore Swiss tourism data from discover.swiss, with per-object attribution and licence filtering.

Korean-aware Google search and place discovery server using Serper API. Features include web search, Naver blog/cafe search, and a unique discover_places tool that generates queries from Korean area and category to extract place names.

Enables conversational exploration of California restaurant data, vibe-based recommendations, and access to structured restaurant details and reviews.

Enables agents to search a public PubMed-derived corpus by natural language or identifiers and to retrieve publication details while traversing bounded citation and semantic literature graphs.

Discovers and routes across 251+ x402-enabled payment services with smart routing strategies (cheapest, fastest, most trusted) and signed attestations. Provides real-time health monitoring, facilitator compatibility checks, and service quality scoring for the x402 agent payment ecosystem.

Enables AI assistants to interact with Watson Discovery, listing projects and collections, and executing natural language queries.

MCP server for discovering, triaging, and monitoring arXiv papers with transparent interest modeling and inspectable ranking.

Enables discovering and independently validating scholarly metadata from extracted research text using Crossref, OpenAlex, DataCite, and optional read-only Zotero checks, returning ranked and verified reference candidates.

Enables fast, zero-configuration statistical exploration of any DuckDB, Parquet, or CSV datasets—computing exact Pearson correlations, ranking drivers against a target variable, and detecting regression outliers in under 200ms. It offers three unified modes (pair verification, exhaustive driver scans, and serendipitous cross-domain discovery) with optional per-capita normalization to remove spurious correlations.

Enables AI agents to search and discover data across SQLite and CSV sources through an MCP interface, with metadata indexing and fuzzy search capabilities.

Discovers and queries x402-payable APIs at runtime — enables autonomous agents to find, evaluate, and pay for services via USDC micropayments on Base without API keys or subscriptions.

Enables AI agents to create parametric geometry, apply loads, run simulations, and read results in Ansys Discovery through natural-language commands over gRPC.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables users to start from a seed host, traverse CDP/LLDP neighbor evidence and device information over SSH, and produce an editable Draw.io topology diagram plus supporting evidence for engineer review. It supports explicit host/CIDR scoping, bounded depth and device counts, strict host-key checks, and a read-only command policy, with an offline simulated demo.

Enables scanning Java/Maven projects to generate TOGAF-standard architecture deliverables (Excel and PPTX) via natural language commands.

A comprehensive MCP server for automated AWS data discovery, PII detection, and data governance using Lake Formation.

An MCP server that provides access to Google's API Discovery Service, allowing agents to discover and interact with Google APIs through natural language commands.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

A meta-MCP server that discovers and explores other MCP servers using progressive disclosure patterns to reduce token usage by up to 99%.