"A search for information or tools related to image processing" matching MCP servers:

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

The Search MCP Server enables seamless integration of network and local search capabilities in tools like Claude Desktop and Cursor, utilizing the Brave Search API for high-concurrency and asynchronous requests.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

A semantic search system for Claude Code transcript history, exposed as an MCP server so Claude Code can query its own past sessions.

A local web search MCP server supporting parallel, API, and model-based search modes, integrating Zhipu Web Search API and online models for real-time information retrieval.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.

Provides hybrid search (BM25 + vector) and staleness reporting for local markdown notes, exposing search and indexing tools to AI assistants via MCP.

Free web search and page fetching for AI agents. No account or API key required. Connect to https://search.parallel.ai/mcp over Streamable HTTP. Tools: web_search and web_fetch. Free-tier rate limits apply.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.