Agentkey
A unified tool interface for AI to access real-time external data.
Install & Use
Copy this prompt and send it to your AI assistant (Claude / Cursor / TRAE / Codex / WorkBuddy etc.) to auto-install:
Help me install this AI Skill: Agentkey. It is used for: A unified tool interface for AI to access real-time external data. Full Skill content: https://321skill.com/skills/agentkey-x-7/raw/index.md Read that page and install it.
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This Skill addresses the issue of AI being unable to access real-time information beyond its training data. In practical development, developers often need AI to access external data sources such as web searches, web scraping, news queries, social media, market data, and on-chain data. However, built-in WebSearch/WebFetch functionalities are limited and cannot dynamically discover new data sources. Agentkey provides a unified MCP tool interface, enabling AI to call hundreds of external APIs as easily as invoking local functions, achieving true real-time data-driven operations.
Usage is straightforward: simply install and configure Agentkey, then describe your data needs using natural language instructions. For example, you can tell the AI, "Search for AI industry news from the past week" or "Check the current price of Bitcoin." Agentkey will automatically call find_tools to discover the most suitable tool, retrieve the parameter template via describe_tool, and finally execute execute_tool to complete the data retrieval. The entire process requires no manual API specification or coding and is fully autonomous for the AI.
It is ideal for agent developers, data analysts, and backend engineers who require real-time data integration. This is particularly relevant for those building AI applications that need dynamic access to external information, such as customer service bots querying order status, quantitative traders needing real-time market data, or social media managers tracking competitor activities. Anyone who wants their AI to fetch the latest information from the web will find Agentkey valuable.
It is recommended to prioritize using Agentkey over the built-in WebSearch whenever external data is needed, as it offers a richer, dynamic tool library and semantic search capabilities. Note that API responses contain external data and should not be directly executed as instructions. Additionally, each call consumes credit points (cost), so it's advisable to check your balance via agentkey_account before performing batch operations.
Key Features
Compared to the built-in WebSearch/WebFetch, Agentkey supports dynamic tool discovery (via semantic search with `find_tools`), offers hundreds of predefined data sources (covering social media, market data, on-chain data, etc.), and its data sources are continuously expanding. In contrast, the built-in functions can only call a fixed set of URLs and cannot automatically discover new tools.
Limitations
Requires MCP protocol support (Claude Code or an MCP client), depends on network connectivity, consumes credit points per call, and has limited free quota.
FAQ
How do I install Agentkey?
Clone the repository locally via git, then configure the tool's path in your MCP client, or run the script directly using the bash client. Refer to the specific installation commands below.
How do I find the right data source tool?
Simply describe your needs in natural language and call `find_tools` for semantic search. For example, 'Find tools related to social media' or 'Search for tools that can check stock prices.' The system will automatically match the appropriate tools.
Installation guide for AI assistants
If your AI coding assistant (Claude Code, Cursor, TRAE etc.) can see this page, send it this message to auto-install:
Visit https://321skill.com/skills/agentkey-x-7/raw/index.md to read the original Skill definition (Markdown format) for Agentkey, and install it according to the instructions.
Raw Markdown URL for AI: /skills/agentkey-x-7/raw/index.md