Retrieve WiFi regulatory limits including max power, EIRP, DFS requirements, and channel plans for any band, protocol, and region.
AGPL 3.0
666,567 tools. Updated 2026-10-16 19:26
"MCP (Model Context Protocol) requirements and selection" matching MCP tools:
- Extract structured, agent-friendly job posting summaries from Open Job Protocol documents, including requirements, compensation, and process details.MIT
- Extracts and structures git diff data, providing context and analysis instructions for AI models via the Model Context Protocol in Lucidity MCP.Apache 2.0
- Access comprehensive guides and documentation for Model Context Protocol development, covering topics like getting started, building servers/clients, core concepts, and best practices.MIT
- Retrieve Model Context Protocol documentation on topics like overview, resources, tools, and setup to build MCP servers correctly.MIT
- Retrieve a compact semantic model of the current design context, including selection, parent containers, siblings, layout, tokens, and off-canvas elements, to support AI-driven design decisions.MIT
Matching MCP Servers
- AlicenseNot gradedqualityDmaintenanceMCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.Apache 2.0
- AlicenseNot gradedqualityDmaintenanceA production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.1MIT
Matching MCP Connectors
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- Retrieve VRAM requirements, context window size, and tier classification for AI models to optimize resource allocation and model selection decisions.-
- Get static protocol info: network specifics, contract addresses, asset list, docs, and AGENTS.md guide for integration and strategy.-
- Get public metadata and explicit Creative Commons requirements for one Sketchfab model.-
- Scaffold a complete Model Context Protocol (MCP) server including tools, resources, prompts, server.py, pyproject, smoke-test client, and README from a plain-English request.MIT
- Corrects sample selection bias with a two-step selection model, using outcome and selection equations to yield unbiased estimates and certified parity evidence.MIT
- Verify a solution against requirements, test criteria, and context to determine if it meets acceptance conditions.-
- Engage in AI-driven conversations with customizable model selection to enhance communication and context understanding. Ideal for integrating intelligent dialogue into workflows.GPL 3.0
- Store organizational context and complex operational requirements to maintain project state for backend development workflows.-
- Fetch public metadata and explicit Creative Commons requirements for a Sketchfab model by its ID.-
- Find keyword mentions in AI model outputs from ChatGPT and Google AI. Returns mention context and sources.MIT
- Shrink the active pixel selection inward by a specified pixel amount. Use to tighten loose selections or trim halos after expanding; create a selection first if none exists.MIT
- Soften the edges of the active pixel selection to create soft transitions before filling, masking, or deleting.MIT
- Save the active pixel selection as a new alpha channel to preserve it for later reload or batch workflows. Requires an active pixel selection.MIT
- Inject relevant context using hybrid BM25 and embedding search. Falls back to BM25 when embeddings are unavailable, ensuring reliable context selection for tasks.Apache 2.0
- Probe a URL for L402 payment requirements. Get the invoice, price in sats, and format to know access costs before paying.MIT