awesome -api

This MCP server acts as a hub of ready-to-use APIs designed for AI agents, LLM workflows, automation, scraping, and integration pipelines. It aggregates various capabilities that can be invoked by consuming MCP endpoints through your agent or orchestration layer. Typical usage involves starting the server locally or in your environment, then sending requests to the exposed MCP tools to perform tasks such as data extraction, web scraping helpers, or automation routines. The server is intended to streamline access to multiple APIs from a single context, enabling agents to enrich their context, fetch structured data, or perform computations as part of a larger workflow.

Capabilities you can expect include: data extraction helpers that parse websites, document-to-markdown transformations, translation and localization utilities, browser automation helpers, and a suite of domain-specific scrapers and analyzers. Integrations are designed to be pluggable, so you can compose tools into higher-level workflows—e.g., fetch product details, normalize and store results, and trigger downstream actions.

Prerequisites:

• Node.js (>= 14) installed on your machine
• Git available to clone the repository
• Basic command line familiarity

Step-by-step installation:

1. Clone the repository: git clone https://github.com/kawsarlog/awesome-mcp-api.git cd awesome-mcp-api

2. Install dependencies: npm install

3. Configure environment variables if needed (see additional_notes for common vars).

4. Start the MCP server: node server.js

5. Verify the server is running by hitting the default MCP health endpoint (http://localhost:PORT/health) or by following the repository's usage guidance for your environment.

If you prefer a different startup method, adapt the steps to your environment (e.g., using a process manager like PM2 or running via a container).

Tips and common considerations:

• Check if the server exposes a health/ready endpoint to ensure it’s up before integrating with your agents.
• If you rely on external services, set appropriate API keys and secrets through environment variables and keep them secure.
• Review rate limits and usage quotas for any integrated APIs to avoid throttling.
• Consider using a process manager in production (e.g., PM2, systemd) to ensure the MCP server restarts on failure.
• If you update dependencies, run npm install again and test that all MCP tools initialize correctly.
• Document any custom endpoints or tools added to your instance for your team to reference.