Motivegrid Vehicle Advisor

BlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.

MCP server for interacting with Neon Management API and databases

Daily, Ed25519-signed security intelligence for AI-agent stacks: CVEs, supply-chain incidents and advisories (GHSA/CISA-KEV/OSV/NVD + national-CERT) assessed for MCP/LLM-proxy impact, cross-validated and signed. Paid via x402 ($0.10 USDC on Base); free sample, list_available, check_affected, get_since.

Dual-market GEO platform. 8 MCP tools for AI visibility audit, citation tracking

AI research MCP — company intel, competitive analysis, industry, topic, person, web scrape

MotiveGrid Vehicle Advisor is a Model Context Protocol (MCP) server that provides structured, data-grounded vehicle intelligence for AI assistants. It enables ChatGPT, Claude, and other MCP-compatible tools to compare cars, evaluate long-term ownership cost, analyze safety and driver-assistance ratings, and generate personalized vehicle recommendations based on real constraints like budget, family size, and usage patterns. Unlike generic web search, MotiveGrid returns structured, decision-ready outputs built on real automotive datasets (including depreciation, fuel economy, and safety ratings), helping AI assistants give consistent, non-hallucinated car buying advice. What you can do with it: Compare vehicles side-by-side (e.g., Toyota RAV4 vs Honda CR-V) Get 5-year total cost of ownership breakdowns Retrieve structured vehicle scorecards (safety, reliability, comfort, efficiency) Generate ranked recommendations based on user needs and budget Explore electric vs hybrid vs gas tradeoffs with grounded data Designed for: AI assistants (Claude, ChatGPT, Cursor, etc.) Developers building automotive tools Users making real-world car buying decisions Key principle: All outputs are grounded in structured automotive data and designed to reduce hallucinations in AI-generated vehicle advice.

MCP server for the IOTA blockchain — 20 tools for AI agent integration: wallet, Move CLI, and on-chain operations.

Repository management, file operations, and GitHub API integration

GitLab API, enabling project management

Model Context Protocol server that integrates AgentQL's data extraction capabilities.

- [sageveterinary/sage-mcp-public](https://github.com/sageveterinary/sage-mcp-public) 🐍 ☁️ - Public MCP server for veterinary diagnostic imaging. 8 tools: provider directory (800+ facilities across 41 states), pricing, locations, educational content, and clinical resources for dogs and cats. Remote SSE server, no auth required.

First Israeli podcast vertical MCP server. 7 read-only tools exposing live data on studios, podcasts, glossary, and the State-of-Israeli-Podcasts 2026 industry report. Languages: Hebrew, English, Arabic, Russian. Operator: Pody (Wikidata Q139719199). License: MIT (server) + CC-BY-SA (data).

Polarion ALM MCP server for Claude, Cursor & Copilot — read and write documents, work items, and traceability links

QuickBooks Online MCP server for Claude Code — 8 automation tools (invoices, payments, reports) that replace ~50K-token UI snapshots.

KaliCart Global is a keyless, read-only MCP server that lets AI agents search a federated catalog of products across independent WooCommerce stores. Each merchant runs the KaliCart Bridge plugin and remains the source of truth for price, stock, and checkout; the global layer provides a single agent-facing search surface over those stores. Results carry merchant-authoritative prices, canonical category leaves, availability status, and per-merchant data-access signals so agents know whether catalog data is live or an indicative snapshot. Tools: - global_search — federated product search across all participating merchants (free text in any language, plus brand, color, price-range, and in-stock filters) - lookup_merchant — check whether a domain runs an ARC-compliant catalog and its federation status

Publish HTML to a private, unguessable URL from any MCP client. Gate by password or email domain; replace in place.

基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"

MCP Advisor & Installation - Use the right MCP server for your needs

Zhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.

Flag features directly from chat in your code editor, including VS Code, Cursor, Windsurf, Claude Code—any IDE with MCP support.

Browser automation and web scraping

AI image generation using various models

Generate styled map images via mapnetwork.app

Create artifacts with your AI tool, publish with Docklet. Turn AI-generated pages, demos, proposals, and guides into live links that people can open, review, and comment on — no exports, hosting setup, or file handoffs. Docklet keeps feedback attached to each artifact and shows real engagement, so you know what people actually viewed, not just what you sent. Go from generated output to reviewable experience without leaving your AI tool.

A local MCP server that exposes Bazel build system capabilities to AI assistants. ## Tools | Tool | Description | |------|-------------| | `bazel_query` | Run arbitrary `bazel query` expressions | | `list_targets` | List targets in a package or subtree | | `get_deps` | Direct or transitive dependencies of a target | | `get_rdeps` | Reverse dependencies within a scope | | `show_target_info` | Rule definition via `query --output=build` | | `bazel_build` | Run `bazel build` | | `bazel_test` | Run `bazel test` with structured results | | `explain_build_file` | Read BUILD file contents for analysis |

Read-only database access with schema inspection

A Model Context Protocol server that provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.