"Local RAG system for providing documentation to a large language model (LLM)" matching MCP servers:

Enables MCP clients to scan local GGUF models, estimate VRAM and suggest GPU offload layers, manage llama-server lifecycle, and proxy OpenAI-format chats with idle auto-unload.

Lets Claude Code send prompts to a locally running Qwen model on Apple Silicon and get answers back, with optional thinking mode for harder problems. It also lists the registered models and reports whether each one is running.

Optimizes token costs by intelligently delegating low-complexity tasks to local LLMs via LiteLLM, enabling cost-effective development workflows.

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

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

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.

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 ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.

Enables AI assistants to search and read Azure documentation using full-text search and section filtering, with content retrieval from Microsoft's official Azure docs repository.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables coding agents to inspect Python applications, research source and target models, and produce reviewable migration plans with evidence gates and evaluation before production code changes.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

A Model Context Protocol server that provides AI assistants with plain-English access to official Dallas-area public data (weather alerts, school ratings, and 311 service requests) without requiring API keys or logins.

Enables AI agents to search, read, annotate, and manage a local Zotero library via the Model Context Protocol, with full local storage and no cloud dependency.

Local-first Microsoft Outlook MCP server: a single Go binary that manages calendar events and mail through the Microsoft Graph API over stdio, with tokens stored in the OS keychain and no Entra ID app registration required. Exposes four aggregate tools (calendar, mail, account, system) dispatched by an operation verb, with multi-account support and read-only and mail-gating modes.

Enables RAG over messy PDFs — extract, chunk, embed, and search scanned, multi-column, and table-heavy documents.

An MCP server that exposes tools for sub-agent style reasoning across multiple LLM providers, enabling delegation of prompts to various models and running critique loops, debates, red-teaming, and answer ranking.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Searches local markdown files using TF-IDF retrieval and serves full documents as resources.

Enables agents to perform local metasearch, scholarly and code/model lookups, and fetch rendered web pages or PDFs as paginated markdown, including stealth browsing and arXiv paper overviews.