19,306 MCP servers crawled across 12 categories. 164 deterministic detection rules. Evidence chains, not vibes.
Official Integrations
Browse all →CLI to run MCP server from Social Shots project
MCP-Server der AI-Agents Zugriff auf Social-Media-Trends gibt (Reddit, HackerNews)
Socket MCP server for scanning dependencies
SodaBOS — The AI-Native Business Operating System. A cognitive substrate where humans use the GUI and AI agents plug in via MCP. Thinks, dreams, learns, asks.
Cross-network DeFi API data, AMM analytics, and SDK docs for 17+ networks.
Sodium Practice Management MCP server — lets AI assistants interact with your Sodium tenant
A Model Context Protocol (MCP) server for interacting with Microsoft 365 and Office services through the Graph API
محتوى تقني متميز في مختلف مجالات هندسة البرمجيات عن طريق تبسيط المفاهيم البرمجية المعقدة بشكل سلس وباستخدام صور توضيحية مذهلة
SoilWise is an AI + IoT-powered agricultural system that helps farmers make data-driven decisions for better yield, sustainability, and profitability. Using soil sensors, satellite imagery, and market data, the platform evaluates soil health, predicts rainfall trends, and recommends optimal crop and fertilizer plans — while also scoring farm-level financial and sustainability performance. It combines six smart modules: 🧠 Soil Analysis: Automated detection of soil type, pH, and nutrient balance. 🌾 AgriShield: Disease recognition and treatment recommendation using computer vision. 💧 IrrigAIte: Smart irrigation planning based on moisture data and local weather. 📈 Yield Predictor: ML-powered yield forecasting and credit scoring for farmers. 🤖 AgriChat: Conversational assistant for personalized advice. 📚 Research Checker: Validates agricultural research claims using AI evidence synthesis. 🧩 MCP Architecture Flow INPUTS ↓ [MCP Logic Layer] ↓ OUTPUTS Input Layer: 1.Soil sensor data (pH, moisture, nutrients) 2.Satellite imagery and weather forecasts 3.Farmer financial & field data (size, crop history) 4.Market data from open agri APIs MCP Logic Layer: 1.Data preprocessing & cleaning 2.AI models (soil classification, disease detection, rainfall prediction) 3.Predictive analytics for yield and credit scoring 4.Generative AI for chatbot and recommendations Output Layer: 1.Personalized crop and fertilizer plans 2.Financial risk and creditworthiness insights 3.Rainfall and yield forecasts (3-month horizon) 4.Interactive chatbot responses and visual dashboards ⚙️ What the MCP Does The MCP acts as the intelligent orchestration layer that links soil data, AI models, and farmer interfaces. It performs: 1.Real-time soil and satellite data processing 2.Cross-model inference for health and yield prediction 3.Dynamic decision generation (recommendations, warnings, or irrigation plans) 4.Data logging for continuous model improvement 🔗 How It Connects to the Client Frontend: Streamlit dashboard and SMS interface (via Africa’s Talking) MCP Server: Python backend (FastAPI + Streamlit) hosted on Azure Cloud MCP Node Data Pipelines: Pulls from satellite APIs (Google Earth Engine), local sensor input, and OpenAI for natural language reasoning Client Access: Farmers, agronomists, and cooperatives can log in or subscribe via mobile or web for real-time guidance 💡 Why It’s Useful or Creative 1.Transforms soil and environmental data into instant, actionable insights — no labs or delays. 2.Integrates AI, IoT, and financial scoring, giving farmers a holistic view of soil health + profitability. 3.Localized intelligence: Tailored to microclimates and soil types in Sub-Saharan Africa and North Africa (Tunisia pilot). 4.Scalable Design: Modular MCP architecture supports easy deployment across regions and languages. 📊 Financial & Credit Scoring Module a.Uses soil productivity metrics and yield forecasts to estimate farmer creditworthiness. b.Generates a SoilWise Credit Score to help farmers access loans or subsidies. Predictive metrics include: 1.Historical yield potential 2.Input efficiency 3.Sustainability index 4.Financial resilience model 🚀 Deployment a.Prototype Deployed: https://soilwise-prototype.streamlit.app/soilwise b.Backend Host: Azure Cloud with integrated MCP server c.Regions Tested: Western & Central Kenya (pilot), expanding to Tunisia for semi-arid adaptation d.Data Sources: Open Data Africa, Google Earth Engine, FAO Soil Database 📁 Repository 🔗 GitHub: https://github.com/antonie-riziki/SoilWise 🏷️ Tags / Categories #AI #Agritech #IoT #MCP #SoilHealth #ClimateResilience #SustainableFarming #CreditScoring
Jinko is a travel MCP server that provides hotel search and booking capabilities.
An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.
Integrates with Solana blockchain to enable natural language querying of account data, transactions, and network status.
Search Solana documentation to quickly find concepts, guides, and examples. Inspect on-chain state by fetching balances, accounts, transactions, blocks, and slots. Create and manage wallets, sign messages, and request testnet airdrops to speed up development.
Fetches and parses Solana blockchain documentation, enabling real-time access to development information for accurate query responses and blockchain-related assistance.
Solana MCP for wallets, trades, markets, PnL, transfers, onchain data, signable swaps and API tools.
solana mcp sever to enable solana rpc methods
On-chain Solana payments for MCP services with SOL and USDC support.
Solana DEX pool liquidity depth — TVL, slippage, volume, Raydium/Orca/Meteora. x402.
Solana priority fees at 6 levels, cost in SOL/USD, congestion. x402.
Real-time Solana token risk scoring and pump.fun graduation signals for AI assistants and trading agents. Built by Sol, an autonomous AI agent. 6 tools: get_token_risk (0-100 risk score + rug pull flags), get_momentum_signal (BUY/SELL based on buy/sell ratios), batch_token_risk (screen up to 10 tokens), get_full_analysis (combined risk + momentum verdict), get_graduation_signals (live pump.fun BUY/SKIP decisions), get_trading_performance (win rate + PnL stats). No auth required — direct HTTP endpoint.
New Solana token launches — pump.fun, Raydium, PumpSwap. Price, liquidity, volume. x402.
Solana wallet health analysis platform and top-notch dev tool. Helps people and agents to recover their SOLs from burner and old wallets super securely. Features a complete trustless recovery flow natively via MCP: preview yields, build unsigned transactions, and sign locally.
MCP server for SOLAPI document search and integration