"Blender MCP: Possible Uses and Contexts" matching MCP servers:

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

Exposes design system component documentation to LLM clients via MCP, allowing listing and retrieving component contexts from Markdown files with YAML frontmatter.

Structured .aide spec files that give AI agents progressive disclosure into your codebase architecture via MCP.

MCP server for the Jaringan protocol that allows AI agents to fetch, inspect, search, and manage Jaringan pages through structured tool calls.

A powerful MCP server for querying and processing large Swagger/OpenAPI JSON documents, enabling LLMs to efficiently access API documentation without loading entire files.

An MCP server that enables searching for Rust crates and their documentation from docs.rs, allowing AI agents to find required crates and access the latest documentation.

Enables MCP-aware agents to fetch documentation pages, strip navigation noise, convert HTML to clean markdown, and emit or return timestamped .md files ready for LLM contexts.

Enables LLM agents to search, read, and query Salesforce documentation across 129 domains. Uses a pre-compiled knowledge graph with 53,000 nodes and 18,000 code snippets for instant retrieval without RAG.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

MCP server for Hugeicons integration and documentation This is a TypeScript-based MCP server that provides tools and resources for integrating Hugeicons into various platforms. It implements a Model Context Protocol (MCP) server that helps AI assistants provide accurate guidance for using Hugeicons

Provides read-only RAG retrieval, document access, source auditing, status, and health checks for CUMCM optimization and decision modeling contexts.

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.

Searches and fetches real-time documentation for libraries like Langchain, OpenAI, and Llama-Index using the Serper API. It allows LLMs to access up-to-date technical information and bypass knowledge cut-off limitations.

A MCP server for interacting with Aptos documentation and creating full-stack Aptos blockchain applications.

Empowers AI agents to securely read and extract information (text, metadata, page count) from PDF files within project contexts using a flexible MCP tool.

Enables vector similarity search and serving of Svelte documentation via the MCP protocol, with support for local caching and multiple llms.txt documentation formats.

Enables authoring, validating, inspecting, blackbox-inventorying, tracing, and capability-querying SPEC.md documents through MCP tools over stdio JSON-RPC. Each tool wraps the same command modules the CLI uses and returns identical JSON envelopes.

Public read-only MCP server for SubcueAI, the AI interview assistant for macOS and Windows. Exposes live pricing and the latest desktop version as tools, plus product overview and FAQ resources. Includes a zero-dependency stdio bridge and Dockerfile.