"RISC-V" matching MCP servers:

Provides LLMs with comprehensive knowledge about the V programming language, including documentation access, code examples, standard library reference, and syntax explanations to help users learn and work with V.

MCP server for see-u-ui component library, allowing AI assistants to query component props/events/slots/examples on demand.

A standalone local MCP server that serves HeroUI v2 component documentation, source code, style definitions, and theme tokens by fetching directly from the official GitHub repository.

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

Enables searching J-Quants API endpoints, retrieving detailed documentation, generating executable sample code, and answering FAQs via MCP clients like Claude Desktop.

MCP server that recommends which npm/PyPI libraries to use or avoid, with concise verdicts, alternatives, and code snippets, keeping responses under 500 tokens.

Provides LLMs with real-time access to up-to-date documentation from PyPI, npm, crates.io, GoDocs, DockerHub, GitHub, and GCP, preventing outdated code generation and API hallucinations.

Enables AI clients like Claude Desktop to search J-Quants API endpoints, get detailed information, reference implementation patterns, and access FAQ answers using MCP.

A beginner-friendly Model Context Protocol (MCP) server that helps users understand MCP concepts, provides interactive examples, and lists available MCP servers. This server is designed to be a helpful companion for developers working with MCP. Also comes with a huge list of servers you can install.

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

Helps migrate projects from AI SDK 4.x to 5.0 by generating a migration checklist and searching the official migration guide for code and data changes.

Enables programming agents to retrieve internal R&D documentation with traceable, reproducible evidence through the MCP protocol, supporting multi-corpus routing and access control.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

An OpenAPI-driven MCP agent hub that dynamically generates MCP tools from Swagger/OpenAPI specs, enabling conversational interaction with backend APIs through natural language.

A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.

Enables AI agents to look up official EYD Edisi Kelima spelling rules and check or correct Indonesian text for common errors such as nonstandard prepositions, particles, affixed forms, and punctuation through tool calls.

Enables Language Models to interact with Notion workspaces through standardized tools for searching, reading, creating, and updating pages and databases.

Automates generation of Work Breakdown Structure (WBS) diagrams and project documents. Supports Mermaid, PNG, and .docx export for project MINTRANET.

Enables AI assistants to interact with OpenAPI documents for analysis, validation, and management through structured interfaces.