"A server to build a knowledge base of Node.js packages with RAG search functionality" matching MCP servers:

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Provides semantic search over a self-building personal technical knowledge base that automatically collects and distills content from GitHub Trending, AI news, and arXiv.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

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

Exposes the Grok Build CLI as MCP tools for Claude Code and other clients, enabling headless AI agents to perform tasks like code reviews, web research, and file operations with configurable permission levels.

MCP server for Google's Gemini File Search (RAG). Manage file search stores, upload documents, and query with RAG through 12 tools.

Live X (Twitter) and web search for any coding agent through your existing Grok subscription. Exposes a grok_search MCP tool, so no X API key or X developer account is needed.

A multi-agent RAG MCP server that answers questions from your documents with a human-in-the-loop approval step, using a coordinator, retriever, and synthesizer agents.

AI-powered MCP server for file renaming, organization, and PDF splitting using natural language prompts and content analysis.

Structured reasoning MCP server that decomposes problems into atomic steps (premise, reasoning, hypothesis, verification, conclusion) with confidence scoring, live visualization, and approval feedback.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Enables document-based Q&A with multi-modal RAG, hybrid retrieval, knowledge graph reasoning, and multi-agent orchestration via MCP tools.

Enables querying multiple AI models simultaneously and returns all answers unmerged for the user to weigh.

Enables indexing a folder of documents or uploaded files into a Qdrant vector store and retrieving relevant chunks with cosine similarity, metadata filters, and heuristic reranking. Exposes rag_stats, rag_search, and rag_index tools over HTTP and Streamable HTTP MCP so clients can fetch ready-to-use context blocks without any built-in chat model.

Exposes a self-contained RAG retrieval pipeline as standard MCP tools, letting Claude Desktop, Cursor, or any MCP client run semantic search over a local knowledge base and fetch index statistics entirely offline without an external LLM. It also ships production hardening out of the box, including Bearer authentication, token-bucket rate limiting, health and Prometheus metrics endpoints, and prompt-injection defenses for retrieved content.

Enables local coding agents to delegate reasoning, planning, review, derivation, and diagnosis tasks to ChatGPT Web through Chrome DevTools Protocol, with security guards and evidence-based verification.

Enables MCP clients to query a modular RAG knowledge hub with hybrid dense/sparse retrieval, reranking, multimodal image support, and traceable observability, all through natural language tools.