Browse the catalog

Enables Cursor on your laptop to connect to an MCP server on EC2 via SSE/HTTPS to manage a task queue stored in Postgres, supporting task listing, status updates, and work prompt generation.

Exposes NeuralVerge's full API as MCP tools for AI research, extraction, agents, and data enrichment (LinkedIn, email, phone), enabling any MCP-compatible client to call them directly.

Provides LLM tools to search, read, and edit Google Drive, Docs, and Sheets, including automatic export to Markdown/CSV and safety features like read-before-write guards.

WeatherForensics is a Data as a Service (DaaS) that provides comprehensive historical weather data, including standard conditions and severe weather events, relative to a specified target location and timestamp. While most services focus on the "what," our proprietary engine calculates the localized impact of historical weather events—ranging from localized tornadoes to regional hurricanes—at a specific coordinate and datetime. Visit the GitHub repository at https://github.com/markwkiehl/WeatherForensics-MCP to access the sample Python client script (mcp_client_noaa.py). That script will allow you to interact with the WeatherForensics Model Context Protocol (MCP) server. No registration or API Key required for the "Forever Free" Tier. To use the WeatherForensics Model Context Protocol (MCP) directly within Claude Desktop, you must bridge its local standard input/output (stdio) requirement to our remote Streamable HyperText Transfer Protocol (HTTP) server. You do this by pointing Claude Desktop to the included proxy script. Add the following to your `claude_desktop_config.json` file: { "mcpServers": { "weatherforensics": { "command": "python", "args": [ "/absolute/path/to/WeatherForensics-MCP/mcp_stdio_proxy.py" ], "env": { "WeatherForensics_API_KEY": "" } } } } - Leave `WeatherForensics_API_KEY` blank to use the Forever Free subscription tier. - Ensure you replace `/absolute/path/to/` with the actual directory path to the cloned repository on your local machine.

MCP server for AI agent trust verification, enabling agents to verify identities, check trust scores, and build reputation across multiple blockchain and web platforms.

MCP server for Dokploy that dynamically generates 420+ tools from the Dokploy OpenAPI spec, enabling deployment, management, and monitoring of self-hosted infrastructure through AI assistants.

Spectra Finance MCP server: yield discovery, PT/YT, looping, Morpho, 10 chains

MCP server to run locally with VS code as client

MCP server for the Shiftyasan public solver API, letting AI agents validate and solve shift-scheduling problems, with async job polling for large cases.

Enables AI agents to interact with live Shopify stores through Admin and Storefront APIs for tasks like GraphQL execution, bulk operations, and file uploads. It includes built-in rate limiting and operation logging to manage store data and schema discovery securely.

A zero-friction stdio MCP bridge connecting Cursor Desktop to a local Hermes Agent, enabling natural language task delegation with session continuity and profile awareness.

A standalone MCP server that validates and cleans structured data returned by AI agents, removing invented fields, coercing incorrect types, and ensuring the output matches the expected schema before it enters your pipeline.

An MCP server that provides tools for financial analysis using the Financial Modelling Prep API. It enables users to retrieve real-time stock quotes, financial statements, valuation metrics, and sector performance data for investment research.

Provides access to Korean government public comparison test data, including product rankings, safety ratings, and recall information from Korea Consumer Agency and Consumer24. Enables agents to search and retrieve verified test results and official sources.

TriMet MCP — live arrivals, stop lookup, vehicle positions and service

Provides a security layer for AI agents with configurable guardrails and policy enforcement. Validates and filters agent actions before execution to prevent unintended operations.

A FastMCP-powered Expense Tracker server that enables AI assistants to manage personal finance data through structured tools. It supports expense tracking, categorization, budget monitoring, transaction retrieval, and financial insights via a standardized MCP interface, making expense management accessible through natural language interactions.

MCP server providing LangGraph agent patterns and code snippets. Use with Claude Desktop, Cursor, or any MCP client.

This Semantic Scholar API MCP server, built with FastMCP, provides a streamlined interface for AI assistants to access academic literature through the Semantic Scholar database. Developed to bridge the gap between AI systems and scholarly research, it offers tools for querying papers, authors, and citations. The implementation stands out by leveraging FastMCP's efficient request handling and Semantic Scholar's comprehensive academic database. By exposing Semantic Scholar's capabilities through standardized MCP endpoints, it allows AI systems to easily incorporate up-to-date research findings and bibliometric data. This server is particularly useful for enhancing AI assistants with academic research capabilities, supporting literature reviews, trend analysis in scientific fields, or building applications that require access to scholarly information.

Integrates with Runbook to allow listing, reading, searching, creating, and updating documents, as well as managing workflow processes.