MCP server for healthcare claims workflow scoring, validation, and feedback, supporting denial risk, prior authorization, and reimbursement assessment.
Signal Found is a Reddit-native B2C/B2B outreach platform. You describe your product, we find people on Reddit already asking for it, and your AI agent handles the rest — messaging prospects, tracking replies, and optimizing your funnel in real time.
Startup engineering acceleration signals for VC investors. Tracks commit velocity, contributor growth, and repo expansion across 20 sectors via public GitHub data. No API key required.
Provides AI agents with direct access to SEC filing intelligence, company fundamentals, dilution risk scoring, and cross-company analytics for financial research.
Bitcoin market intelligence MCP server. Exposes Signal Lord's composite gauge scoring, on-chain and macro regime signals, and market data to AI agents.
Interactive, streaming SSH tool for LLM agents that enables spawning long-running remote commands with live line-by-line output, signal handling, stdin input, and SFTP file transfer.
Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.
Local-first inspectable memory substrate for Claude Code. Three read-only MCP tools (search_pairs, compact_session, substrate_info) over a signal-scored parse of ~/.claude/projects/, zero outbound calls.
Provides XGBoost-based directional predictions (UP/DOWN) for EURUSD and GBPUSD forex pairs via MCP tools, including feature extraction and signal generation.
A persistent, stateful MCP server that exposes a detached tmux session to clients, enabling shell command execution, terminal buffer reading, and control signal sending via JSON-RPC over stdio.
An MCP server that exposes macOS-native device trust signals — the facts about a Mac that cannot be gathered from a Linux container or a cloud runner. All tools are strictly read-only.
A content exploration MCP server that helps LLMs surface high-signal, unsummarized web content through clean APIs and Markdown conversion, with intelligent frontmatter steering and citation tracking.
A Python MCP server that reduces token usage by ~98% when working with log files by auto-detecting format and stripping noise to return only actionable signal.