# Context Repo — Resources

> Section-level llms.txt for the /resources article surface. In-depth
> articles on AI context management, MCP servers, prompt versioning,
> semantic search, and integrations across Claude, Cursor, and ChatGPT.
> For the site-wide context pack see /llms.txt and /llms-full.txt.

## Articles

- [How MCP Servers Connect AI Agents to Knowledge Bases](https://contextrepo.com/resources/how-mcp-servers-connect-ai-agents-to-knowledge-bases): A grounded look at the Model Context Protocol, what an MCP server actually does, and how Context Repo's 28-tool MCP server connects Claude, Cursor, ChatGPT, and 90+ AI clients to your context repository.
- [Prompt and Document Management for AI Agents](https://contextrepo.com/resources/prompt-and-document-management-for-ai-agents): How a context repository handles the day-to-day mechanics of prompts and documents that AI agents actually consume: version history, variable interpolation, semantic search, and 75+ file formats over MCP and REST.
- [Semantic Search and Deep Search: Two Retrieval Layers](https://contextrepo.com/resources/semantic-search-and-deep-search-two-retrieval-layers): Why Context Repo ships both a catalog-level semantic search and a hierarchical chunk navigator, and how to pick the right one for the question your AI agent is actually asking.
- [Using Context Repo with Claude, Cursor, and ChatGPT](https://contextrepo.com/resources/using-context-repo-with-claude-cursor-and-chatgpt): How a single context repository travels across Cursor, Claude Desktop, Claude.ai, and ChatGPT. Real workflows for the engineer, the researcher, and the operator, plus the Chrome extension that feeds all three.
- [What Is an AI Context Repo for Agents?](https://contextrepo.com/resources/what-is-an-ai-context-repo-for-agents): What an AI context repository is, what belongs inside it, and how Context Repo gives humans and agents one home for prompts, documents, and collections across every AI tool.

## Markdown alternates

- [How MCP Servers Connect AI Agents to Knowledge Bases (markdown)](https://contextrepo.com/resources/how-mcp-servers-connect-ai-agents-to-knowledge-bases.md)
- [Prompt and Document Management for AI Agents (markdown)](https://contextrepo.com/resources/prompt-and-document-management-for-ai-agents.md)
- [Semantic Search and Deep Search: Two Retrieval Layers (markdown)](https://contextrepo.com/resources/semantic-search-and-deep-search-two-retrieval-layers.md)
- [Using Context Repo with Claude, Cursor, and ChatGPT (markdown)](https://contextrepo.com/resources/using-context-repo-with-claude-cursor-and-chatgpt.md)
- [What Is an AI Context Repo for Agents? (markdown)](https://contextrepo.com/resources/what-is-an-ai-context-repo-for-agents.md)

## Feeds & indexes

- [RSS feed](https://contextrepo.com/resources/feed.xml): Article updates via RSS 2.0
- [Site-wide llms.txt](https://contextrepo.com/llms.txt): Top-level discovery file
- [Full agent context pack](https://contextrepo.com/llms-full.txt): Extended context for agents
- [Documentation index](https://contextrepo.com/docs/llms.txt): Section-scoped llms.txt for user documentation
- [REST API index](https://contextrepo.com/api/llms.txt): Section-scoped llms.txt for the /v1 REST API
- [Developers index](https://contextrepo.com/developers/llms.txt): Section-scoped llms.txt for SDK and MCP integrators

## When to read these articles

Read these when you need long-form context on how Context Repo works -
the design intent behind features, the trade-offs we made, and the
workflows the product supports. These are not API reference docs; for
those, start at https://contextrepo.com/docs/api and https://contextrepo.com/openapi.json.