"Setting Up MCP (Minecraft Control Panel or Related Tool) Helper" matching MCP servers:

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.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

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 agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

An MCP server that retrieves relevant code snippets and documents to assist in generating pymilvus code, converting between ORM and client, and translating Milvus code between programming languages.

An MCP server designed to assist with generating, converting, and translating Milvus SDK code by retrieving relevant documentation and snippets. It supports PyMilvus code generation, ORM-to-client conversion, and cross-language translation between Python, Java, Go, and other supported languages.

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.

MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.

An MCP (Model Context Protocol) server that chains calls to other MCP tools, reducing token usage by allowing sequential tool execution with result passing

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.

Enables dynamic tool discovery and loading for Claude using BM25, regex, and semantic search algorithms. It supports managing a catalog of over 10,000 tools with minimal context overhead and provides a REST API for tool management.

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

Exposes search over internal documents and company lookup via authenticated API, enabling LLMs to access firm files and data.

Enables managing and controlling AnythingLLM instances through MCP, providing tools to list, create, and delete workspaces, retrieve system environment settings, and get vector counts.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

Provides semantic search, note retrieval, source explanation, daily digests, and health checks for a local Obsidian vault, enabling MCP clients like Claude Desktop and Claude Code to query the second brain via natural language.

Transforms prompts into Chain of Draft (CoD) or Chain of Thought (CoT) format to enhance LLM reasoning quality while reducing token usage by up to 92.4%, supporting multiple LLM providers including Claude, GPT, Ollama, and local models.

Enables local data discovery by indexing metadata from SQLite, CSV, and Markdown sources, providing hybrid keyword and TF-IDF semantic search via MCP tools (listSources, indexSource, search, getSchema) and a REST API.

Enables searching, ingesting, and querying academic papers using natural language, with integration to arXiv and Semantic Scholar.

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.