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

Enables AI coding assistants to query private academic paper collections via standard MCP tools, with hybrid retrieval, reranking, and inline citations.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

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.

An MCP server that retrieves relevant PDF chunks via local embeddings and returns them to IDE agents (Cursor, Kiro, Claude Code) for answer generation.

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

Enables agents to search across the pooled tools of many connected MCP servers and invoke them through a single endpoint, returning only the handful of tools relevant to each request. Filters by the caller's permissions before ranking, so agents never see or plan around tools their user is not allowed to use.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.

Enables MCP-compatible clients to perform retrieval-grounded Q&A over FordA dataset notes and safe arithmetic calculations through callable tools.

An MCP server providing web search, image search, and page scraping tools to LLMs without requiring API keys.

Enables MCP clients to query a document knowledge base with permission-aware hybrid retrieval, listing sources, searching snippets, and fetching document context while reporting confidence for each result.

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.

A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

Crawl any documentation site and return heading-bounded, LLM-ready chunks with source metadata for Pinecone, Chroma, pgvector, LangChain, or LlamaIndex.

Scores AI outputs for faithfulness, relevancy, and hallucination inside any MCP client, with custom metrics, golden sets, and run history with dashboards.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

The MCP server provides tools for entity extraction, query refinement, and relevance checking to enhance RAG applications by integrating with OpenAI and Gemini.

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.

Enables enterprise knowledge search through a chat interface, comparing traditional RAG with MCP-driven retrieval using hybrid BM25 and dense vector search, Ollama-powered answer generation, and question routing to domain-specific retrieval tools.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.

Enables full-text search and paginated retrieval of indexed documentation (PDFs, Markdown, text) through MCP tools, with filtering by category and file.

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

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.

Integrates the LINE Messaging API with AI agents via the Model Context Protocol, supporting both stdio and SSE transport protocols. It allows agents to send messages, manage rich menus, and retrieve user profile information for LINE Official Accounts.

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 web page scraping via Jina reader API and searching FastMCP documentation using minsearch. Supports fetching markdown content from URLs and querying indexed documentation files.

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

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

Enables an ElevenLabs support agent to call support tools over MCP, including Discord ticket flows, post-call webhook handling, and knowledge-base syncing.

Enables AI clients to list, inspect, triage, and update support tickets via MCP tools, with a mocked dataset designed for swapping in real ticket sources later.

A server for Model Context Protocol (MCP) that uses Server-Sent Events (SSE) for streaming communication, enabling tools like the HackerNews API to be accessed through a secure HTTP+SSE transport.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

A Model Context Protocol server that exposes multiple AI tools over SSE transport with JWT-based secure authentication, allowing for dynamic tool registration and session management.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables post-hoc auditing of an agent's retrieval supply chain by recording digest-only provenance from source through chunk, transformation, context and decision, then reporting influence rankings with an honest unexplained residual, lineage traces, advisory source trust and retirement recommendations, and retrieval schema drift. It never performs retrieval, ranks documents at query time, or blocks decisions.

An evaluation harness that probes MCP-based retrieval servers for calibration, relevance, coverage, citation integrity, and more, also exposing the probes as MCP tools for assistants and CI agents.

Enables an AI operator to create consent-based remote support sessions on Windows PCs, run PowerShell commands, and upload or download files through an audited, self-terminating MCP relay.

Enables agents to search a shared index through MCP, returning token-budgeted results filtered by each user's access permissions.

An SSE-based MCP server for retrieving real-time weather data for a specified location, supporting current conditions and forecasts.