#rails

Give your AI agents a wallet they can't abuse. Almega is an MCP server that puts a control layer in front of every payment: per-agent spending limits, allow-listed categories, 1-click human approval on sensitive transactions, and a full audit ledger. Two backends ship in one file — `memory` (zero-config, 30-second demo) and `stripe` (real Stripe Issuing test-mode virtual cards, no real money). 7 tools, stdio transport, Python 3.10+, MIT.

Local guardrail proxy for AI coding agents. Wraps any MCP server (stdio or Streamable HTTP) and blocks destructive tool calls — DROP TABLE, rm -rf, force-push — before they execute. TOFU catalog pinning against rug pulls, plus tool-poisoning and result-injection scanning. Single Rust binary, Apache-2.0.

Runtime security oracle for AI agents — scan prompts, tool calls, and outputs before execution. Pay-per-call via x402/USDC, no accounts needed.

One shared AI setup for your team. Stop losing prompts in chats and docs. Save one shared setup, tailor it for your team, and use it across ChatGPT, Codex, Claude, Figma, and more.

A single `forecast` tool your agent calls before any irreversible action (send money, run SQL, delete data, post content). Returns a risk score (0–100), a reversibility class, named red flags from 28 failure modes, and a gate: proceed / confirm / human-required.

ThumbGate is an agent governance MCP server that prevents costly AI mistakes before they execute. It provides pre-action gates, shared lessons across agents, and team-level safeguards for AI coding workflows. Features include Thompson Sampling for intelligent decision-making, feedback loops, and integrations with Claude, Cursor, and OpenCode.

Runtime policy enforcement for AI agents. Evaluate every agent action against your organization's policies before execution. Define policies once in the Hejdar dashboard, enforce everywhere via MCP. Supports observe mode (shadow/audit) and enforce mode (real-time blocking).

Enterprise AI Control Plane — governance layer between your AI applications and providers. Spend tracking, runtime guardrails, policy enforcement, budget limits, compliance readiness (SOC2/GDPR/HIPAA), and real-time provider health. Works with Claude, ChatGPT, Copilot, and any MCP-compatible client.

Younanix Memory MCP gives autonomous AI agents access to real-world engineering memory from actual incidents (Slack threads + GitHub issues in Supabase, TRPC, Drizzle, Rails, Node.js etc).Natural language tool: query_lessons (search for problems, root causes, solutions) Structured output: {problem, root_cause, lesson_learned, confidence (80-100%), category, tags} Free preview: 1 query/hour (degraded results) Full access: $0.10 per query via x402/USDC micropayments (permissionless, no API keys needed) 1000+ lessons live, auto-growing from public repos Connect once in Cursor/Claude Desktop/Windsurf → your agent auto-queries high-confidence fixes without hallucinations. Perfect for debugging, performance, security, reliability in real stacks. Site: https://www.younanix.com Let's make agents smarter with battle-tested knowledge! #AIAgents, #MCP ,#Debugging

Automatically introspects your Rails application and exposes schema, models, routes, controllers, views, auth, tests, config, and conventions to AI assistants via MCP. 9 read-only tools, zero configuration. Works with Claude Code, Cursor, Windsurf, and GitHub Copilot.

Scout Monitoring's local MCP server empowers AI Assistants by integrating application performance and error data directly into their workflows. It allows AI models to access traces, errors with line-of-code information, and performance insights like N+1 queries, slow endpoints, and memory bloat from various frameworks including Rails, Django, and FastAPI. This direct data access enables AI Assistants to identify and suggest fixes for performance problems and errors right within your editor and codebase, significantly enhancing development efficiency and reducing debugging time.

Enable AI assistants to explore and query your Turbot Guardrails data!

A minimal Rails API template for creating MCP (Model Context Protocol) servers with robust tool execution capabilities and examples.

MCP servers in your Rails app

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