"Semantic Web" matching MCP servers:

MCP server for searching web documentation via sitemap.xml, enabling semantic search across multiple documentation sites using Ollama embeddings.

MCP server for semantic search over PDF documents using RAG, pgvector, and OpenAI embeddings. Includes a web app for document upload and management.

A fast, dependency-light MCP server that converts web pages into clean Markdown, structured metadata, and classified links for language models.

MCP file cache for AI coding agents. Re-reading an unchanged file costs ~40 tokens instead of the whole file; a changed file comes back as a diff. Adds grep, BM25 search and glob over cached files, atomic edits with dry_run, and token-budgeted batch reads. One local daemon serves every client. No API keys, no GPU. Works with Claude Code, Cursor, VS Code, Codex and OpenCode.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.

Local semantic recall MCP server for citation-integrity workflows. Enables semantic search over a text corpus, returning file paths and page numbers for verification, with 100% local processing using ONNX embeddings and LanceDB.

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 natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

Enables AI agents to query verified-emissions knowledge graphs in natural language and validate data against supported standards, with metered billing and optional verified identity.

Enables AI agents to fetch any web page and receive clean, token-efficient Markdown, escalating only as needed from direct HTTP with browser TLS fingerprints to headless-browser rendering and residential proxies when a site blocks access. Supports question-focused passage retrieval with BM25 ranking, pagination, caching, JS rendering control, and safe-by-default restrictions on local and private-network URLs.

An enterprise-grade Model Context Protocol server for high-performance web analysis that discovers subpages, provides AI-based page summaries, and extracts structured content for RAG using FastMCP and FastAPI.

A focused MCP server that provides a single web_search tool for web searches, integrating Tavily and Brave with automatic fallback and key rotation.

MCP server that fetches web pages and uses local Qwen models to answer questions about their content, with site-scoped search and map-reduce chunking for long pages.

Shared research cache for AI agents. Caches web research across sessions and users - hit means instant answer from verified sources, miss means your research saves the next dev's tokens. Semantic search with freshness tracking, gap detection, and real-time token measurement via JSONL. Free, open source.

Semantic code search for any MCP client: indexes local folders of code and docs and answers plain-language or code queries with matching passages, file paths, line ranges and scores. Embedding runs on the local CPU with the Motherlode code-search encoder, so no file content leaves the machine; the encoder downloads once from Hugging Face. Install: npx -y blackwindow-weave-mcp.

Enables semantic search over local markdown specs, RFCs, and docs using Ollama and LanceDB, allowing AI agents to find relevant information by meaning rather than exact keywords.

Provides web search capabilities to Claude AI using the Anthropic API, allowing LLMs to access up-to-date information from the web with customizable domain filtering.