"Aggregated RSS Feed Curation and Quality Control Tools" matching MCP servers:

Enables agents to discover feeds for a site, retrieve dated feed items as clean JSON, and perform keyless news searches across Google News and Bing News with deduplication and publisher attribution.

Professional RSS/Atom feed management system with AI-powered analytics including sentiment analysis, trend detection, auto-categorization, cross-source verification, automated scheduling, and content export capabilities.

Enables AI agents to screen and filter stock universe, compute custom quality scores, inspect score history, manage scoring systems, and generate shareable screen links, acting as the signed-in user.

Model Context Protocol Server for aggregating RSS feeds in Claude Desktop

Enables interaction with RSS readers that support the FreshRSS API through natural language. Allows users to manage and query their RSS feeds and articles via LLM conversations.

MCP server for US (Mississippi) and UK government procurement feeds. Search live bids and tenders and track what changed over time: deadline moves, new awards, and added documents. Tools: search_opportunities, get_opportunity, list_recent_changes.

Enables LLMs to orchestrate AI agents and tasks, inspect DAG workflows, monitor cluster metrics, and perform safe database queries and statements through standardized MCP tools.

Enables intelligent RSS feed management with AI-powered semantic search, advanced filtering, and a comprehensive reading workflow. Supports OPML parsing, article organization with status tracking, and token-efficient browsing of large feed collections.

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Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

Enables AI assistants to inspect and safely control OBS Studio over obs-websocket v5, exposing scenes, inputs, filters, outputs and video settings as read and write tools that default to dry runs and refuse changes while live unless explicitly confirmed. It also provides Source Record and IRL readiness checks, a BRB auto-switcher, and a scene timeline log for cutting clips from VODs.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Enables local/remote execution infrastructure through the official Codex Runtime, providing shell, files, Git, sessions, browser, computer use, recoverable tasks, multi-host routing, dynamic MCP integration, and skill lifecycle management.

Transforms any API into an intelligent MCP agent in seconds, enabling natural language interaction with APIs through the Model Context Protocol.

Enables AI agents to perform common utility tasks through a streamable HTTP MCP endpoint, including JSON inspection, regex testing, cron parsing, hashing, base64 encoding/decoding, URL analysis, color conversion, text diffing, CSV parsing, JWT decode/verification, Markdown-to-HTML rendering, and UUID/token generation without API keys.

Enables users to describe a project in an MCP client and work through pre-submission grant phases, including finding fitting programs, checking eligibility and blockers, pulling precedent from past awards, shortlisting, and drafting memos, budgets, and submission checklists. Coverage is full for US grants and partial (discovery and precedent only) for Canada, with no win-odds estimates or post-award reporting.