ZBS Index What actually exists in applied AI, with the source next to it

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.

What this server can do

2 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

find_awesome_section(limit, query, confidence)
Discovers sections/categories across awesome lists matching a search query and returns matching sections from awesome lists. You MUST call this function before 'get_awesome_items' to discover available sections UNLESS the user explicitly provides a githubRepo or listId. Selection Process: 1. Analyze the query to understand what type of resources the user is looking for 2. Return the most relevant matches based on: - Name similarity to the query and the awesome lists section - Category/section relevance of the awesome lists - Number of items in the section - Confidence score Response Format: - Returns matching sections of the awesome lists with metadata - Includes repository information, item counts, and confidence score - Use the githubRepo or listId with relevant sections from results for get_awesome_items For ambiguous queries, multiple relevant sections will be returned for the user to choose from. Required: query.
get_awesome_items(listId, offset, tokens, section, githubRepo, subcategory)
Retrieves items from a specific awesome list or section with token limiting. You must call 'find_awesome_section' first to discover available sections, UNLESS the user explicitly provides a githubRepo or listId.

Last successful function declaration observed on . Source: https://www.context-awesome.com/api/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://www.context-awesome.com/api/mcp.

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
mcp tools declared 2 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe www.context-awesome.com
mcp endpoint status ok The server listed 2 functions when asked. as of probe www.context-awesome.com

Where to get it

Related, by what their authors tagged them

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.

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

GET /api/v1/entries/mcp_server.json

Sources

  1. bh-rat/context-awesome on GitHub — GitHub, observed , trust tier 3.
  2. Official MCP Registry — Model Context Protocol, observed , trust tier 1.
  3. Tools declared by the MCP server at https://www.context-awesome.com/api/mcp — www.context-awesome.com, observed , trust tier 1.