Defi Mcp

A Model Context Protocol Server connector for Perplexity API, to enable web search without leaving the MCP ecosystem.

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.

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

Revdoku lets Claude, Codex, ChatGPT, and other AI agents publish generated reports, dashboards, prototypes, documents, and interactive app sites as real websites. Sites can be public, password-protected, or mapped to your own domain; regenerating keeps the same URL.

summarize chat message

Secure file operations with configurable access controls

Repository management, file operations, and GitHub API integration

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.

Web content fetching and conversion for efficient LLM usage

A Serper MCP Server

Web and local search using Brave's Search API

The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve data without writing custom database queries. This integration facilitates seamless access to vector data, enhancing the capabilities of AI tools like Claude Desktop and Cursor.

Payment security for AI agents. Allowance lets agents request human-approved virtual cards, complete checkout, and report receipts without exposing a real card.

Channel management and messaging capabilities

Local-first persistent memory for AI coding agents over MCP. Gives Claude Code, Cursor and Codex shared, durable project memory across sessions. No cloud, no API keys.

OpenBase is a free MCP server that gives any AI assistant instant access to data on 20M+ French companies — no API key and no signup required. It serves official French open data from INSEE, INPI, BODACC, DECP and Judilibre through 14 ready-to-use tools: company search and full profiles (SIREN/SIRET), directors and executives, financial statements and ratios, solvency scores, legal announcements, public contracts, court decisions, corporate ownership networks, and aggregated business signals (hiring, funding, public grants). Ideal for company lookup, due diligence, KYC, B2B prospecting and financial analysis. The fastest way to connect French business intelligence to Claude, Cursor and other AI agents — free, instant, open data.

One API for Search, Crawling, and Sitemaps

Retrieving and analyzing issues from Sentry.io

An MCP server that resolves under-specified, half-remembered queries for AI agents into verified answers — or an honest decline. Built on the principle that it never returns a confident-wrong: when it can't resolve with confidence, it shortlists honestly or declines rather than guessing. Free remote endpoint, streamable HTTP transport.

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

Browser automation and web scraping

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

Search 2,972 premium domains for sale, inspect current asking prices and buyer paths, and submit purchase offers directly to the seller.

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.

Obfuscate Python & reverse-map stack traces from your agent. AST-based, no phone-home. PyArmor alt.