"A server/tool for RAG-based documentation scraping and retrieval with SSE support" matching MCP servers:

Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Enables AI agents to parse PDFs and search local document context through multimodal extraction and vector-based retrieval, all exposed as MCP tools.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

An open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

Search and retrieve Agent2Agent (A2A) protocol documentation using full-text search and section filtering.

An MCP server that provides utility tools for text analysis, URL metadata fetching, and temperature conversion.

Enables access to AWS documentation through natural language by fetching and converting documentation pages to markdown, searching AWS docs, and getting content recommendations for AWS service documentation.

Enables local-first hybrid knowledge retrieval from authorized Markdown and plain-text files, combining full-text and vector search with reranking and traceable source references via a single search tool.

MCP server for Claude Code that generates a documentation skeleton from Git repository changes, outputting a Markdown file with placeholders for AI analysis.

Provides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.

Provides e-commerce customer support tools for order status, delivery, account, and policy questions, with RAG-grounded retrieval and strict authorization checks over mock data.

Enables searching and reading OCI documentation using the Oracle Help Center Search API. Provides tools for finding relevant documentation URLs and reading page content.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.

MCP server for AI-native L1 support: triages tickets, answers from a knowledge base, escalates to L2 via Telegram/GitHub, and manages feedback, with a LangGraph workflow and safety guardrails.

Manages the state of a chess game for LLMs/agents without suggesting moves, providing tools to create/reset game, add moves, get status, and check legality.