Hello 
Here it is and let me know what you think.
After comparing the detailed overview of Hive technologies from the article with your current MCP server implementation, here are my suggestions:
Current Status: Your MCP server currently implements basic post retrieval (get_posts_by_tag, get_posts_by_user), but doesn't leverage the full power of Hivemind's social data capabilities.
Recommendation: Expand your social data tools with Hivemind-specific endpoints that would allow AI to:
Community Analytics: Add functions to retrieve community statistics, subscriber lists, and moderation actions.
get_community_info - Get detailed information about a Hive community
get_community_members - Retrieve subscribers/members of a community
get_community_statistics - Get posting and engagement metrics for a community
Follow Network Analysis: Add capabilities to analyze social graphs:
get_followers - Get a list of accounts following a user
get_following - Get a list of accounts followed by a user
get_mutual_followings - Find accounts that are mutually followed between users
Social Reputation Tools: Add reputation analysis functionality:
get_reputation_details - Get detailed breakdown of a user's reputation metrics
get_top_contributors - Find top contributors in a tag or community based on reputation
Benefits: This would give AI assistants a much deeper understanding of the social layer of Hive, making them more useful for community managers, content creators, and curators.
Current Status: Your MCP server doesn't appear to leverage the Hive Application Framework capabilities.
Recommendation: While HAF integration might require access to private databases, you could add support for querying public HAF applications through their APIs:
HAF App Interface: Create a generic tool to interact with HAF apps:
query_haf_app - Call public endpoints of HAF applications
Custom Schema Access: For organizations running their own HAF instances, you could provide database-level access through a configuration option.
Considerations: This feature might have limited utility for public users, as many HAF applications might be private. However, for developers or organizations running their own HAF apps, this could be very valuable.
Current Status: Your MCP server offers basic account and post retrieval but doesn't support complex analytics queries.
Recommendation: Add analytics tools that leverage HiveSQL's capabilities:
Advanced Analytics Tools:
run_blockchain_analytics - Execute predefined analytical queries (common metrics, trends)
generate_account_report - Create comprehensive analytics report for an account
analyze_tag_performance - Get performance metrics for specific tags over time
Historical Data Mining:
search_historical_content - Search the full history of Hive posts by keywords
find_content_trends - Identify trending topics or tags over specified time periods
Benefits: These tools would transform your MCP server from a simple data fetcher into a powerful analytics platform, giving AI assistants the ability to provide deep insights from blockchain data.
Current Status: Your MCP server focuses on core Hive functionality but doesn't integrate with Hive Engine's sidechain.
Recommendation: Add support for Hive Engine's token ecosystem:
Token Management Tools:
get_token_info - Get information about a specific Hive Engine token
get_token_balance - Get a user's balance of a specific token
get_token_market - Get market data for a token (price, volume, orders)
Token Transfer Operations:
send_token_engine - Send Hive Engine tokens to another account
stake_token - Stake a stakeable Hive Engine token
NFT Support:
get_nft_info - Get information about an NFT on Hive Engine
get_nft_collection - Get information about an NFT collection
get_nft_holdings - Get NFTs owned by a specific account
Benefits: This would dramatically expand the usefulness of your MCP server by allowing AI assistants to work with the entire Hive ecosystem, not just the core blockchain.
Current Status: You already have some great cryptography features like sign_message, verify_signature, encrypt_message, and decrypt_message.
Recommendation: Expand these capabilities with:
Multi-signature Support:
create_multisig_transaction - Create a transaction requiring multiple signatures
sign_multisig_transaction - Add a signature to a pending multisig transaction
Enhanced Messaging:
create_private_thread - Create a secure conversation thread with another user
manage_conversation_history - Retrieve and manage encrypted conversation history
Benefits: These advanced security features would be particularly useful for business users and those requiring enhanced privacy.
Current Status: Your MCP server implements various Hive operations but doesn't include development assistance tooling.
Recommendation: Add tools to help developers work with Hive more effectively:
Code Generation:
generate_hive_code - Generate example code for common Hive operations in multiple languages
validate_hive_operation - Validate a custom operation before broadcasting it
Transaction Simulation:
simulate_transaction - Test what would happen when executing a transaction
estimate_transaction_cost - Calculate the resource credits required for an operation
Benefits: These tools would make your MCP server valuable not just for end-users but also for developers building on Hive.
While the article presents many exciting possibilities, there are practical reasons to be selective about which integrations to implement:
Private Database Access: HAF and Hivemind integrations may require access to private databases, which isn't feasible for a public MCP server.
Maintenance Overhead: Supporting too many services increases the complexity and maintenance burden.
Security Considerations: Direct access to databases (like HAF or Hivemind) could pose security risks if not properly implemented.
Performance Concerns: Some integrations like complex HiveSQL queries could be resource-intensive and might require rate limiting.
Based on the analysis, here's a suggested priority order for new features:
Your hive-mcp-server project already provides a solid foundation of Hive blockchain functionality. By strategically implementing some of the technologies discussed in the article, particularly Hive Engine integration and enhanced social analysis tools, you could significantly expand its capabilities without overcomplicating the codebase.
The most important consideration should be user needs - prioritize the features that will provide the most value to your target users, whether they're content creators, community managers, developers, or casual Hive users.
Would you like me to elaborate on any specific area of these recommendations or provide more detailed implementation suggestions for any of the proposed features?
RE: What Hive tech should be integrated into an MCP?