4everland/4everland-hosting-mcp
MCP ServerFree** - An MCP server implementation for 4EVERLAND Hosting enabling instant deployment of AI-generated code to decentralized storage networks like Greenfield, IPFS, and Arweave.
Capabilities9 decomposed
mcp-based hosting service integration with decentralized storage backends
Medium confidenceImplements a Model Context Protocol (MCP) server that exposes 4EVERLAND Hosting APIs as standardized tool calls, enabling LLM agents and AI code generators to directly invoke deployment operations without custom HTTP client code. The MCP abstraction layer translates tool schemas into backend API calls, supporting multiple decentralized storage networks (Greenfield, IPFS, Arweave) through a unified interface that abstracts network-specific implementation details.
Bridges MCP protocol with decentralized storage networks through a unified tool schema, allowing LLMs to deploy code to Greenfield/IPFS/Arweave without understanding network-specific APIs or transaction mechanics
Unlike traditional hosting APIs that require custom client libraries per network, this MCP server abstracts all decentralized backends behind standardized tool calls, enabling any MCP-compatible LLM to deploy code with a single integration
ai-generated code deployment to decentralized storage with automatic backend selection
Medium confidenceAccepts AI-generated code artifacts (from code generation models or agents) and automatically routes them to the optimal decentralized storage backend based on file size, cost, and latency requirements. The system handles file staging, network-specific transaction preparation (gas estimation for Greenfield, IPFS pinning configuration, Arweave bundling), and returns a unified deployment result with gateway URLs and content identifiers across all backends.
Implements intelligent backend routing logic that evaluates file size, cost, and latency to automatically select between Greenfield, IPFS, and Arweave, abstracting network-specific transaction mechanics (gas estimation, pinning, bundling) from the deployment caller
Compared to single-backend hosting services, this capability provides automatic cost optimization and multi-network redundancy; compared to manual backend selection, it eliminates configuration overhead for AI-driven deployment pipelines
mcp tool schema generation and registration for 4everland hosting apis
Medium confidenceDynamically generates MCP-compliant tool schemas from 4EVERLAND Hosting API specifications and registers them with the MCP server, enabling LLM clients to discover and invoke deployment operations through standard tool-calling interfaces. The schema generation handles parameter validation, type mapping, and error response formatting to ensure LLM-safe invocation patterns.
Generates MCP tool schemas from 4EVERLAND API specifications with automatic type mapping and validation, enabling LLMs to invoke hosting operations without custom client code or manual schema definition
Unlike hardcoded tool definitions, this approach scales to new APIs automatically; compared to REST API clients, MCP schemas provide LLM-native type safety and discoverability
multi-network decentralized storage abstraction layer with unified api
Medium confidenceProvides a unified abstraction layer that translates deployment requests into network-specific operations for Greenfield (BNB Chain storage), IPFS (content-addressed peer-to-peer), and Arweave (permanent storage), handling protocol differences like transaction signing, fee estimation, and content addressing. The abstraction normalizes responses across networks into a common deployment result format with network-agnostic URLs and metadata.
Abstracts three fundamentally different storage models (Greenfield's blockchain-backed storage, IPFS's content-addressed P2P, Arweave's permanent storage) behind a unified API, handling protocol-specific transaction mechanics, fee estimation, and content addressing automatically
Unlike single-network hosting services, this provides multi-network redundancy and cost optimization; compared to manual multi-network integration, it eliminates boilerplate for transaction signing, fee estimation, and content addressing across heterogeneous protocols
deployment status tracking and content retrieval across decentralized networks
Medium confidenceTracks deployment status across Greenfield, IPFS, and Arweave networks, providing unified queries for deployment state (pending, confirmed, failed) and enabling content retrieval through network-appropriate gateways. The system maintains a deployment ledger that maps deployment IDs to network-specific identifiers and provides normalized status responses regardless of underlying network confirmation semantics.
Provides unified deployment status tracking and content retrieval across three networks with different confirmation semantics, maintaining a deployment ledger that maps deployment IDs to network-specific identifiers and normalizing status responses
Unlike network-specific explorers, this provides a single query interface for multi-network deployments; compared to manual status checking, it abstracts network-specific confirmation semantics and provides normalized status across heterogeneous protocols
authentication and credential management for multi-network deployments
Medium confidenceManages authentication credentials for 4EVERLAND Hosting and multiple decentralized storage networks (Greenfield, IPFS, Arweave), supporting multiple credential types (API keys, private keys, wallet addresses) and providing secure credential injection into deployment requests. The system handles credential rotation, expiration tracking, and network-specific authentication flows without exposing secrets to LLM clients.
Provides unified credential management for heterogeneous authentication schemes across Greenfield (private key signing), IPFS (API key), and Arweave (wallet key), with secure injection into deployment requests without exposing secrets to LLM clients
Unlike manual credential passing, this provides centralized management and rotation; compared to storing credentials in environment variables, it supports secure backend storage and expiration tracking
cost estimation and optimization for multi-backend deployments
Medium confidenceEstimates deployment costs across Greenfield, IPFS, and Arweave based on file size, storage duration, and network fees, providing cost breakdowns and recommendations for backend selection. The system queries real-time or cached fee data from each network and applies heuristics to recommend the most cost-effective backend for given deployment parameters.
Provides unified cost estimation and backend recommendation across three networks with different pricing models (Greenfield: blockchain storage fees, IPFS: pinning costs, Arweave: permanent storage fees), applying heuristics to recommend the most cost-effective option
Unlike manual cost comparison, this automates backend selection based on deployment parameters; compared to single-backend services, it provides cost transparency and optimization across multiple networks
deployment configuration and manifest management with validation
Medium confidenceManages deployment configurations and manifests that specify storage backend preferences, access controls, TTL, and other deployment parameters. The system validates configurations against schema constraints, applies defaults, and provides configuration versioning to track changes across deployments.
Provides schema-based validation and versioning for deployment configurations across multiple decentralized backends, enabling infrastructure-as-code workflows for decentralized hosting
Unlike hardcoded configurations, this enables declarative deployment specifications; compared to manual validation, it provides automated schema checking and version tracking
error handling and deployment failure recovery with retry logic
Medium confidenceImplements comprehensive error handling for deployment failures across Greenfield, IPFS, and Arweave, with network-specific error classification and recovery strategies. The system provides detailed error messages, suggests remediation steps, and supports configurable retry policies with exponential backoff.
Provides network-specific error classification and recovery strategies for Greenfield, IPFS, and Arweave, with configurable retry policies and detailed remediation suggestions
Unlike generic error handling, this provides network-specific error classification and recovery; compared to manual error handling, it automates retry logic and provides detailed remediation guidance
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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mcp.natoma.ai
** – A Hosted MCP Platform to discover, install, manage and deploy MCP servers by **[Natoma Labs](https://www.natoma.ai)**
Best For
- ✓AI agent developers building autonomous deployment workflows
- ✓LLM application builders integrating decentralized hosting into code generation pipelines
- ✓Teams migrating from centralized hosting to decentralized storage networks
- ✓AI code generation platforms (Cursor, GitHub Copilot extensions, custom agents)
- ✓Serverless function deployment systems using decentralized storage as backend
- ✓Web3 development teams building AI-assisted smart contract deployment tools
- ✓MCP server developers integrating 4EVERLAND Hosting into LLM applications
- ✓Teams building internal LLM tools that need dynamic API discovery
Known Limitations
- ⚠MCP protocol overhead adds ~50-100ms per tool invocation due to JSON serialization and transport
- ⚠No built-in retry logic or exponential backoff — requires external orchestration for fault tolerance
- ⚠Limited to tool-based invocation patterns; streaming deployment logs not supported through MCP
- ⚠Requires separate authentication credentials for each decentralized storage backend
- ⚠Backend selection heuristics are static; no dynamic cost monitoring or real-time fee comparison
- ⚠Large code artifacts (>100MB) may exceed IPFS gateway timeouts; requires manual Arweave routing
Requirements
Input / Output
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** - An MCP server implementation for 4EVERLAND Hosting enabling instant deployment of AI-generated code to decentralized storage networks like Greenfield, IPFS, and Arweave.
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