mcp server
Context Awesome
MCP server for accessing curated awesome list documentation
Description as published by the maintainer. Source
- version 0.1.1
- active
- documentation
- document understanding
active — Most recent push to the repository was 2026-06-10. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 57 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-06-10 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 0.1.1 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-06-10 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-06-10 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
github-awesome-copilot-acquire-codebase-knowledge
— last commit 2026-08-06, shares agents, awesome
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompt…
-
github-awesome-copilot-acreadiness-assess
— last commit 2026-08-06, shares agents, awesome
Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.htm…
-
github-awesome-copilot-acreadiness-generate-instructions
— last commit 2026-08-06, shares agents, awesome
Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md…
-
github-awesome-copilot-acreadiness-policy
— last commit 2026-08-06, shares agents, awesome
Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant che…
-
github-awesome-copilot-ad-campaign-analyzer
— last commit 2026-08-06, shares agents, awesome
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prom…
-
github-awesome-copilot-add-educational-comments
— last commit 2026-08-06, shares agents, awesome
Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.
-
github-awesome-copilot-adobe-illustrator-scripting
— last commit 2026-08-06, shares agents, awesome
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating…
-
github-awesome-copilot-agent-skill-stack
— last commit 2026-08-06, shares agents, awesome
Find, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Us…
-
github-awesome-copilot-agentic-workflows
— last commit 2026-08-06, shares agents, awesome
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
-
github-awesome-copilot-ai-prompt-engineering-safety-review
— last commit 2026-08-06, shares agents, awesome
Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security v…
These share tags the maintainers applied themselves, such as agents, awesome. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: agents, awesome, awesome-list, llm, mcp, mcp-server.
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