"Fishing Conditions for Tomorrow" matching MCP servers:

AgentPay — x402 crypto data gateway on Stellar. 10 live pay-per-call tools: token prices, whale activity, gas tracker, DeFi TVL, Fear & Greed, Dune queries, token security. Agents pay USDC on Stellar. No API keys. Budget-aware sessions.

Provides comprehensive weather information including current conditions, 7-day forecasts, and air quality data for any city worldwide using the Open-Meteo API. Features real-time weather data, hourly forecasts, sunrise/sunset times, and European Air Quality Index with human-readable descriptions.

A Model Context Protocol server implementation that enables AI assistants to interact with Slack workspaces, allowing them to browse channels, send messages, reply to threads, add reactions, and retrieve user information.

Execution control layer for AI agents - Reserve, execute, burn/refund pattern for media generation

Merx - TRON Resource Exchange Merx is the first TRON resource exchange that aggregates energy and bandwidth providers into a single MCP server. GitHub: https://github.com/Hovsteder/merx-mcp Hosted SSE: https://merx.exchange/mcp/sse npm: merx-mcp Website: https://merx.exchange Stats * 52 tools, 30 prompts, 21 resources * 7+ energy providers (CatFee, ITRX, PowerSun, Fe

Enables MCP-compatible clients to manage AI agent teams, including agents, Kanban issues, projects, goals, approvals, budgets, and raw API access.

MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!

Enables AI agents to drive real Google Chrome with stealth and captcha handling, using Patchright to avoid bot detection.

Hey @roocode community! I'm thrilled to share a project born from my work with Roocode and the vision of an AI-powered development team: the Anubis MCP Server! This system is heavily inspired by Roocode and designed to orchestrate an AI development workflow based on agile methodology. It simulates

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

Badgr lets AI agents launch GPU workloads, deploy inference endpoints, run models and execute AI workflows through MCP. Route workloads to available compute, track execution and costs, and retrieve verified results without managing GPU infrastructure.

Adds OrgX MCP tools to a DeepSeek Harness profile and runs a workspace-bound OrgX gateway peer through Harness headless mode.

A tool that allows deployment of a Model Context Protocol server on Cloudflare Workers without authentication requirements, enabling users to create and use custom AI tools via the Cloudflare AI Playground or Claude Desktop.

A free, local room where multiple MCP-compatible AI coding agents collaborate on one codebase — collisions prevented, human in command.

A lightweight topological arbitration MCP server for multi-agent clusters, using Topological Data Analysis to resolve decision conflicts and enable consensus among agents.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables an MCP client such as Claude Code to read and operate your real, everyday Firefox profile — reading pages, clicking, typing, navigating, switching tabs and taking screenshots — with per-action human approval and masking of password, one-time-code and credit card fields.

Enables sleeping agents to monitor multiple event sources and wake only when durable composite or temporal conditions are met, supporting derived events and targeted wakeups without keeping an agent loop alive.

Enables multi-agent systems to share and coordinate a common state space over MCP, detecting concurrent mutation race conditions, synchronizing state through vector clocks, and resolving conflicting decisions via consensus arbitration. Also supports deterministic policy validation and cryptographic state hashing with zero external dependencies.

It enables LLM clients to control a browser by giving goals and candidate values while Jev selects elements, actions, and values, with Playwright executing them. It also exposes tools for opening pages, checking conditions, choosing options, taking snapshots, direct actions, reading content, screenshots, WebMCP tools, and closing sessions.