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Provides encrypted, portable memory for AI agents via MCP, allowing fact storage, conversation recall, and cross-machine sync using Arweave.

A Model Context Protocol (MCP) server that provides secure PostgreSQL database integration tools for Claude Code. Features read-only query execution, schema exploration, and performance analysis.

Config-driven MCP server for cross-domain full-text search across agent session logs, meeting transcripts, and notification files.

Wraps Oh My Pi built-in tools (read, write, edit, bash, grep, etc.) as MCP tools, enabling file operations, shell commands, web search, and agent coordination.

Enables AI agents and LLMs to control and monitor Redfish-enabled hardware through power operations, system inventory, event logs, health monitoring, sensor readings, and user account management.

A protocol implementation that extends AI capabilities through a WebSocket interface, enabling mathematical calculations, email operations, knowledge search, and remote device control.

Simple Tempo MCP server that provides integration with Grafana Tempo for distributed tracing analysis through two core tools: tempo_query for searching traces and tempo_trace_detail for retrieving detailed trace information. Built by Elchin Habibov in Go with Docker support, the implementation connects to Tempo instances via configurable TEMPO_URL environment variable and includes Claude Desktop configuration examples for both direct binary execution and Docker-based deployment. Designed for developers and DevOps engineers who need conversational access to distributed tracing data for debugging microservices, analyzing performance bottlenecks, and investigating system issues without manually navigating Tempo's web interface.

This Anti-Bullshit MCP server, developed by Teglon Labs, provides tools for analyzing claims, validating sources, and detecting manipulation using multiple epistemological frameworks. Built with TypeScript and leveraging the Model Context Protocol SDK, it offers empirical, responsible, harmonic, and pluralistic approaches to evaluate information. The implementation focuses on rigorous fact-checking and critical thinking, making it accessible for AI models to assess the credibility and implications of various claims. It's particularly useful for tasks like academic research validation, media literacy enhancement, or combating misinformation in digital content, enabling AI assistants to apply nuanced epistemological analysis without requiring deep expertise in each framework.

An MCP server template for Cloudflare Workers with zero runtime dependencies, providing a hand-rolled Streamable HTTP transport that lets you easily define and deploy tools with static bearer token auth.

Enables AI assistants to query BuiltWith's technology detection data directly, supporting natural language questions about website technologies.

Query money flows between state, citizens, and enterprises. Simulate policy changes, compare cohorts, and check data confidence directly from MCP-compatible tools.

A local MCP server that enables managing Google Contacts via the People API through tools for listing, searching, getting, creating, updating, deleting, and counting contacts. It requires an externally stored OAuth token and confirms all write operations.

MCP server enabling AI assistants to interact with the Qualys vulnerability management platform. Supports investigation, risk assessment, compliance, remediation, security overview, and report management.

Enables running a remote MCP server on Cloudflare Workers with OAuth login, allowing AI clients like Claude to interact with tools via SSE.

This MCP server provides AI-powered restaurant discovery and booking assistance by integrating Google Maps Places API with intelligent recommendation algorithms. Built with TypeScript using the Model Context Protocol SDK, it offers restaurant search with cuisine filtering and location-based queries, AI-driven recommendations that score restaurants based on mood, event type, and user preferences, detailed restaurant information retrieval including reviews and photos, availability checking, and booking instruction generation. The implementation features a sophisticated scoring system that weighs factors like ratings, cuisine matches, price levels, and event suitability to provide contextually relevant restaurant suggestions, making it valuable for dining planning, date night coordination, business meeting venues, and family gathering locations.

This MCP server implementation, developed by Hal, provides a Python server for WeCom (WeChat Work) bots following the Model Context Protocol. Built with FastAPI and leveraging libraries like fastmcp and httpx, it offers a streamlined interface for integrating WeCom bot functionality into MCP-based applications. The implementation focuses on simplicity and ease of use, making it ideal for developers looking to add enterprise messaging capabilities to their AI workflows. It supports core WeCom bot features and can be easily extended. This server is particularly useful for teams using WeCom who want to automate notifications, create interactive chatbots, or integrate AI-assisted communication tools within their existing enterprise messaging infrastructure.

Enables AI agents to discover WordPress plugin opportunities by querying the WordPress.org directory for abandoned, low-rated, or unsupported plugins that can be replaced or out-built.

MCP server for interacting with FreshRSS via the Google Reader API, enabling subscription management, content reading, and item operations.

Enables natural language querying of Korean public medical data (data.go.kr) through MCP clients like Claude, providing tools for searching hospitals, drugs, non-payment costs, disease statistics, and more.

MCP server giving AI agents controlled residential-proxy web access with optional browser rendering and structured extraction from 60+ sites.