"How to create an ag-Grid instance or application" matching MCP servers:

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Enables finding information online, reading web pages, finding images, capturing screenshots, and performing multi-source research with per-answer confidence.

Enables browser automation by managing Selenium Grid browser instances (Chrome, Firefox, Edge) in Docker or Kubernetes environments. Provides secure, scalable browser control for AI agents and testing workflows.

A privacy-first MCP server for locally managing job, fellowship, and graduate-school applications. It offers tools for tracking application status, analyzing role fit, generating LaTeX CV/cover letters, interview prep, and discovering public jobs from ATS APIs.

Provides real-time electricity grid data including CO2 intensity, power mix, and wholesale prices, plus optimal green time windows for energy-intensive AI tasks. Supports UK, Germany, and global regions with optional API keys.

Enables AI assistants to query, filter, and update job application records, and to analyze skill demand across postings.

Enables Claude Web users to manage their job application workflow by storing profile and resume data, analyzing job descriptions, preparing applications, and tracking progress — all with manual submission and no platform automation.

A minimal MCP server using FastMCP to demonstrate tool creation, including a get_weather example.

An MCP server that connects AI assistants to YNAB budgets, enabling natural language queries about finances backed by full API coverage and built-in YNAB methodology knowledge.

Enables AI agents to search and retrieve cited evidence packs for renewable energy assets, analyze locations, and access regional energy context, all from a local DuckDB snapshot of Aragon renewable infrastructure data.

Enables tracking job applications by connecting Gmail to retrieve emails, process job details, manage statuses, and generate statistics.

Enables AI agents to safely execute Python, JavaScript, and Bash code in an isolated Docker sandbox with strict security constraints.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

Enables forwarding Douyin or Bilibili video shares to Kimi for AI analysis and automatically writing the resulting Chinese notes into an Obsidian vault.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.