"A server for finding video editing resources or tools" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables AI agents to perform exact-match, transactional multi-file edits with atomic writes, dry-run diffs, and self-correcting error diagnostics that reduce token usage.

A professional video format conversion tool based on MCP protocol that supports multiple formats, batch processing, and quality control for video files.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Enables an AI agent to screen-record a live Expo app on a connected phone, auto-plan and direct the footage with captions, motion graphics, pop-outs and sound, then export a 1080p MP4. It also opens an interactive studio where users refine scenes by dragging, resizing, or typing prompts, and exposes all app_* control tools from expo-mcp-bridge in the same session.

A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Enables AI agents to pay per call for live package-safety and GitHub merge-readiness trust signals via the x402 protocol.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Enables rigging, animation, and VFX workflows for Roblox through an MCP-compatible chat client, connecting Blender and Roblox Studio for tasks like skeleton fitting, keyframe editing, particle effects, and FBX export.

Exposes AWS Palace finite-element electromagnetic simulation as a set of JSON-in/JSON-out tools, so an agent can build geometry and meshes, generate and lint configs, estimate cost, guard and launch runs, and read back S-parameters, eigenmodes, Q and energy results. Results return as JSON text plus structured content over a dependency-free stdio JSON-RPC connection.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

Provides AI-powered tools to apply UX/UI best practices, Nielsen's heuristics, cognitive biases, and Material-UI patterns to React components. Enables automated application of responsive design, Apple design patterns, and complete UX guidelines through natural language commands.

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

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.