Provides semantic search over ScriptingApp documentation by converting Markdown/MDX files into a LlamaIndex vector store. Supports multi-language indexing and enables natural language queries against technical documentation through MCP tools.
Enables AI assistants to read, write, organize, search, and compile Scrivener writing projects. Supports manuscript editing, document management, consistency checking, and PDF export for writers using Scrivener 3.
Enables automated project analysis and structured development specification generation. Supports multiple export formats and integrates with AI models for comprehensive project documentation and validation.
A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.
Model Context Protocol server that enables AI assistants like Claude to access searchapi.io API for searching Google Maps, flights, hotels, and other web information.
Access Apple's official developer documentation, frameworks, APIs, and WWDC videos through the Model Context Protocol (MCP), support AI driven natural language queries, and provide Swift/Objective-C code examples and technical guidelines.
Model Context Protocol (MCP) server that provides AI agents with access to Google Search Console data.
Provides access to Mozilla's Searchfox code search service, enabling AI assistants to search through Mozilla's codebases and retrieve file contents from repositories like mozilla-central, autoland, and ESR branches.
Enables web search capabilities through the Brave Search API, including web search, local POI lookups, and rich search results retrieval for MCP-compatible clients.
A lightweight and fast MCP server that enables AI agents to efficiently discover and execute tools through progressive disclosure, minimizing context consumption while supporting safe code execution in external environments.
An intelligent movie and TV series resource search tool based on Model Context Protocol (MCP), supporting multi-source search and link verification.
Enables intelligent code analysis and search across repositories using the CodeRank algorithm (inspired by PageRank) to identify critical modules, trace dependencies, find code hotspots, and perform context-aware keyword searches with importance-ranked results.
An MCP server for SearXNG that provides web search capabilities with concise model-visible output while preserving full result payloads in metadata. It supports search, parallel fetching, URL extraction, and research workflows through both local stdio and streamable HTTP transports.
Provides privacy-focused web search capabilities through SearXNG metasearch engine, enabling web, image, video, and news searches without tracking. Includes comprehensive research tools that aggregate and analyze results from multiple search engines.
Captures and organizes structured markdown notes from Claude Code sessions with automatic pattern detection, complexity analysis, advanced search, and weekly reports. Everything runs locally without external dependencies.
For Dynamous members to learn MCP client/server implementation
Enables interaction with decentralized exchanges on the SEI blockchain through natural language commands. Supports token swapping, wrapping, liquidity pool queries, and automated trading strategies on DragonSwap.
Content-addressed vocabulary protocol: 452 cognitive patterns with cryptographic identity. Agents sharing a handle (e.g. StateLock#5602) provably share meaning — mismatched vocabularies halt rather than silently drift.
Reduces token consumption by over 80% through intelligent file caching, returning only diffs for modified files and suppressing unchanged content. It features a suite of 12 tools for semantic search, batch reading, and efficient file editing to optimize LLM interactions with large codebases.
Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.
