"The Models Resource" matching MCP servers:

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

Turns product ideas into rendered UI screen mockups and a buildable component manifest, so downstream agents can develop real screens from the generated designs.

Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.

A local MCP server for read-only querying of AWS resources (Lambda, S3) via Boto3, currently exposing a health check tool with planned tools for listing resources and checking free tier.

Enables AI assistants to interact with humans through GUI dialogs for text input, choices, confirmations, and information display.

Enables MCP clients to interact with Odoo models through generic read and write tools, with read-only mode by default and Odoo ACLs as the authority.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

A Model Context Protocol server for querying and analyzing Azure resources at scale using Azure Resource Graph, enabling AI assistants to explore and monitor Azure infrastructure.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables authorized web/API security analysis as a stateful, multi-stage workflow with persistent session state, human-controlled validation, candidate versus confirmed finding tracking, and stop conditions.

Provides context management, task classification, and routing tools for small models (1B-12B) in production agentic workflows.

Enables ChatGPT to inspect public Instagram, Threads, and web resources through a local browser and return a schema-validated Evidence Packet for evidence-first review.

An MCP server that manages your conversation context automatically, pruning dead branches and keeping an audit trail of every cut.

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.

Enables local-first management of OpenCode model routing, letting users discover, enable, and assign orchestrator/specialist roles to models while safely connecting the chosen policy to OpenCode via a local MCP bridge.

MCP server that lets an AI analyst place real bets on Binance prediction markets, using Kelly criterion sizing, and tracks its performance through a transparent record of betting slips and outcomes.

A local MCP daemon that turns an agentic coding client into a bug bounty operator, with 103 tools for offensive security testing including MITM proxy, traffic analysis, and OOB callbacks.